Mining rich semantic information hidden in heterogeneous information network is one of the important tasks of data mining. Generally, a nuclear medicine text consists of the description of disease (<i>i.e.</i...Mining rich semantic information hidden in heterogeneous information network is one of the important tasks of data mining. Generally, a nuclear medicine text consists of the description of disease (<i>i.e.</i>, lesions) and diagnostic results. However, how to construct a computer-aided diagnostic model with a large number of medical texts is a challenging task. To automatically diagnose diseases with SPECT imaging, in this work, we create a knowledge-based diagnostic model by exploring the association between a disease and its properties. Firstly, an overview of nuclear medicine and data mining is presented. Second, the method of preprocessing textual nuclear medicine diagnostic reports is proposed. Last, the created diagnostic modes based on random forest and SVM are proposed. Experimental evaluation conducted real-world data of diagnostic reports of SPECT imaging demonstrates that our diagnostic models are workable and effective to automatically identify diseases with textual diagnostic reports.展开更多
Ovarian cancer has one of the highest mortality rates among gynecological malignancies.This disease has a low early detection rate,a high postoperative recurrence rate,and a 5-year survival rate of only 40%.Hence,ther...Ovarian cancer has one of the highest mortality rates among gynecological malignancies.This disease has a low early detection rate,a high postoperative recurrence rate,and a 5-year survival rate of only 40%.Hence,there is an urgent need to improve the early diagnosis and prognosis of ovarian cancer.Prediction models can effectively estimate the risk of disease occurrence,as well as its prognosis.Recently,many studies have established multiple ovarian cancer prediction models based on different regions and populations.These models can improve the detection rate and optimize the prognosis management to a certain extent.Herein,the construction principle of the ovarian cancer risk prediction model and its validation are summarized;furthermore,comprehensive reviews and comparisons of the different types of these models are made.Therefore,our review may be of great significance for the whole course of ovarian cancer management.展开更多
To address the challenge of identifying the primary causes of energy consumption fluctuations and accurately assessing the influence of various factors in the converter unit of an iron and steel plant,the focus is pla...To address the challenge of identifying the primary causes of energy consumption fluctuations and accurately assessing the influence of various factors in the converter unit of an iron and steel plant,the focus is placed on the critical components of material and heat balance.Through a thorough analysis of the interactions between various components and energy consumptions,six pivotal factors have been identified—raw material composition,steel type,steel temperature,slag temperature,recycling practices,and operational parameters.Utilizing a framework based on an equivalent energy consumption model,an integrated intelligent diagnostic model has been developed that encapsulates these factors,providing a comprehensive assessment tool for converter energy consumption.Employing the K-means clustering algorithm,historical operational data from the converter have been meticulously analyzed to determine baseline values for essential variables such as energy consumption and recovery rates.Building upon this data-driven foundation,an innovative online system for the intelligent diagnosis of converter energy consumption has been crafted and implemented,enhancing the precision and efficiency of energy management.Upon implementation with energy consumption data at a steel plant in 2023,the diagnostic analysis performed by the system exposed significant variations in energy usage across different converter units.The analysis revealed that the most significant factor influencing the variation in energy consumption for both furnaces was the steel grade,with contributions of−0.550 and 0.379.展开更多
Objective:A risk-based sequential screening strategy,from questionnaire-based assessment to biomarker measurement and then to endoscopic examination,has the potential to enhance gastric cancer(GC)screening efficiency....Objective:A risk-based sequential screening strategy,from questionnaire-based assessment to biomarker measurement and then to endoscopic examination,has the potential to enhance gastric cancer(GC)screening efficiency.We aimed to evaluate the ability of five common stomach-specific serum biomarkers to further enrich high-risk individuals for GC in the questionnaire-identified high-risk population.Methods:This study was conducted based on a risk-based screening program in Ningxia Hui Autonomous Region,China.We first performed questionnaire assessment involving 23,381 individuals(7,042 outpatients and 16,339 individuals from the community),and those assessed as“high-risk”were then invited to participate in serological assays and endoscopic examinations.The serological biomarker model was derived based on logistic regression,with predictors selected via the Akaike information criterion.Model performance was evaluated by the area under the receiver operating characteristic curve(AUC).Results:A total of 2,011 participants were ultimately included for analysis.The final serological biomarker model had three predictors,comprising pepsinogenⅠ(PGI),pepsinogenⅠ/Ⅱratio(PGR),and anti-Helicobacter pylori immunoglobulin G(anti-H.pylori IgG)antibodies.This model generated an AUC of 0.733(95%confidence interval:0.655-0.812)and demonstrated the best discriminative ability compared with previously developed serological biomarker models.As the risk cut-off value of our model rose,the detection rate increased and the number of endoscopies needed to detect one case decreased.Conclusions:PGI,PGR,and anti-H.pylori Ig G could be jointly used to further enrich high-risk individuals for GC among those selected by questionnaire assessment,providing insight for the development of a multi-stage riskbased sequential strategy for GC screening.展开更多
A 2-dimensional global free surface diagnostic model, combined with dynamic calculation, is used to investigate the world ocean circulation; the model has a horizontal resolution of 1/4°×1/4°. The simul...A 2-dimensional global free surface diagnostic model, combined with dynamic calculation, is used to investigate the world ocean circulation; the model has a horizontal resolution of 1/4°×1/4°. The simulated results agree well with the results of other modesl and observations. The distribution of Stream Function suggests that the main circulation systems in the wodd ocean have been represented, including oceanic currents strengthened in the oceanic western. Be close to the observed results, the net mass transport of the Kuroshio axes is estimated about 54Sv; The distribution of the horizontal circulation in each layer shows that the main circulation systems in the world ocean are well simulated, for example, the Kuroshio and the Antarctic Circumpolar Current can go down to the bottom layer, but the Gulf Stream cannot, and its direction reverses at the depths of 1000 to 2 000 m.展开更多
We established a diagnostic model to predict acute Mycoplasma pneumoniae （M. pneumonia） infection in elderly Community-acquired pneumonia （CAP） patients. We divided 456 patients into acute and non-acute M. pneumon...We established a diagnostic model to predict acute Mycoplasma pneumoniae （M. pneumonia） infection in elderly Community-acquired pneumonia （CAP） patients. We divided 456 patients into acute and non-acute M. pneumoniae infection groups. Binary logistic regression and receiver operating characteristic （ROC） curves were used to establish a predictive model. The following independent factors were identified： age 〉 70 years; serum cTNT level 〉 0.0S ng/mL; lobar consolidation; mediastinal lymphadenopathy; and antibody titer in the acute phase 〉 1：40. The area under the ROC curve of the model was 0.923 and a score of 2 7 score predicted acute M. pneumoniae infection in elderly patients with CAP. The predictive model developed in this study has high diagnostic accuracy for the identification of elderly acute M. pneumoniae infection.展开更多
A high resolved two-dimensional linear global diagnostic model combining with the dynamical calculation is used to calculate velocity field in the South China Sea(SCS). The study of model results shows that eddy diffu...A high resolved two-dimensional linear global diagnostic model combining with the dynamical calculation is used to calculate velocity field in the South China Sea(SCS). The study of model results shows that eddy diffusion does not change basic structure of circulation in the SCS and does not change the direction of invasive water, but changes the value of transport considerably especially in straits. The velocity field is not changed whether the wind stress is considered or not. This result shows the circulation is largely determined by a density field which well records most of the important contribution of the wind stress effect. Potential vorticity is calculated to testify the dynamics of the model results. The result shows that a good conservation of the nonlinear PV. This indicates most effects of the important nonlinear processes are well recorded in density and the nonlinear term is negligible so that the simplified model is reliable. The model results show the water exchanges between the SCS and open ocean or surrounding seas. Cold deep water invades through Luzon Strait and Warm shallow water is pushed out mainly through Karimata Straits. The model results also reveal the structure of the circulation in the SCS basin. In two circulations of upper and middle layers, a cyclonic one in the north and an anti-cyclonic one in the south, reflect the climatologic average of the circulation driven by monsoon. In the deep or bottom layer, these two circulations reflect the topography of the basin. Above the middle layer, invasive water enters westward in the north but the way of invasion of Kuroshio is not clear. Below the deep layer, a current goes down south near the east basin ,and invasive water enters in the basin from the west Pacific.展开更多
BACKGROUND Colorectal cancer(CRC)is a major global health burden.The current diagnostic tests have shortcomings of being invasive and low accuracy.AIM To explore the combination of intestinal microbiome composition an...BACKGROUND Colorectal cancer(CRC)is a major global health burden.The current diagnostic tests have shortcomings of being invasive and low accuracy.AIM To explore the combination of intestinal microbiome composition and multi-target stool DNA(MT-sDNA)test in the diagnosis of CRC.METHODS We assessed the performance of the MT-sDNA test based on a hospital clinical trial.The intestinal microbiota was tested using 16S rRNA gene sequencing.This case-control study enrolled 54 CRC patients and 51 healthy controls.We identified biomarkers of bacterial structure,analyzed the relationship between different tumor markers and the relative abundance of related flora components,and distinguished CRC patients from healthy subjects by the linear discriminant analysis effect size,redundancy analysis,and random forest analysis.RESULTS MT-sDNA was associated with Bacteroides.MT-sDNA and carcinoembryonic antigen(CEA)were positively correlated with the existence of Parabacteroides,and alpha-fetoprotein(AFP)was positively associated with Faecalibacterium and Megamonas.In the random forest model,the existence of Streptococcus,Escherichia,Chitinophaga,Parasutterella,Lachnospira,and Romboutsia can distinguish CRC from health controls.The diagnostic accuracy of MT-sDNA combined with the six genera and CEA in the diagnosis of CRC was 97.1%,with a sensitivity and specificity of 98.1%and 92.3%,respectively.CONCLUSION There is a positive correlation of MT-sDNA,CEA,and AFP with intestinal microbiome.Eight biomarkers including six genera of gut microbiota,MT-sDNA,and CEA showed a prominent sensitivity and specificity for CRC prediction,which could be used as a non-invasive method for improving the diagnostic accuracy for this malignancy.展开更多
Presently, research is lacking regarding the diagnosis and evaluation of habitat degradation in enclosed bay systems. We established a diagnostic model for enclosed bay habitat degradation(EBHD model) using a multi-ap...Presently, research is lacking regarding the diagnosis and evaluation of habitat degradation in enclosed bay systems. We established a diagnostic model for enclosed bay habitat degradation(EBHD model) using a multi-approach integrated diagnostic method in consideration of driving force-pressurestate-infl uence-response. The model optimizes the indicator standardization with annual average change rate of habitat degradation as the basic element, to refl ect accurately the impact of the change and speed of degradation on the diagnostic results, to quantify reasonably the contribution of individual diagnostic indicator to habitat degradation, and to solve the issue regarding the infl uence of subjective factors on the evaluation results during indicator scoring. We then applied the EBHD model for the Sansha Bay in Fujian Province, China, evaluated comprehensively the situation of habitat degradation in the bay, and screened out the major controlling factors in the study area. Results show that the diagnostic results are consistent in overall with the real situation of the study area. Therefore, the EBHD model is advantageous in terms of objectivity and accuracy, making a breakthrough in diagnosis and evaluation for habitat degradation in enclosed bay systems.展开更多
Background:Diabetic nephropathy(DN)is the most common complication of type 2 diabetes mellitus and the main cause of end-stage renal disease worldwide.Diagnostic biomarkers may allow early diagnosis and treatment of D...Background:Diabetic nephropathy(DN)is the most common complication of type 2 diabetes mellitus and the main cause of end-stage renal disease worldwide.Diagnostic biomarkers may allow early diagnosis and treatment of DN to reduce the prevalence and delay the development of DN.Kidney biopsy is the gold standard for diagnosing DN;however,its invasive character is its primary limitation.The machine learning approach provides a non-invasive and specific criterion for diagnosing DN,although traditional machine learning algorithms need to be improved to enhance diagnostic performance.Methods:We applied high-throughput RNA sequencing to obtain the genes related to DN tubular tissues and normal tubular tissues of mice.Then machine learning algorithms,random forest,LASSO logistic regression,and principal component analysis were used to identify key genes(CES1G,CYP4A14,NDUFA4,ABCC4,ACE).Then,the genetic algorithm-optimized backpropagation neural network(GA-BPNN)was used to improve the DN diagnostic model.Results:The AUC value of the GA-BPNN model in the training dataset was 0.83,and the AUC value of the model in the validation dataset was 0.81,while the AUC values of the SVM model in the training dataset and external validation dataset were 0.756 and 0.650,respectively.Thus,this GA-BPNN gave better values than the traditional SVM model.This diagnosis model may aim for personalized diagnosis and treatment of patients with DN.Immunohistochemical staining further confirmed that the tissue and cell expression of NADH dehydrogenase(ubiquinone)1 alpha subcomplex,4-like 2(NDUFA4L2)in tubular tissue in DN mice were decreased.Conclusion:The GA-BPNN model has better accuracy than the traditional SVM model and may provide an effective tool for diagnosing DN.展开更多
AIM： To build a clinical diagnostic model of primary open angle glaucoma （POAG） using the normal probability chart of frequency-domain optical coherence tomography （FD-OCT）. METHODS： This is a cross-sectional ...AIM： To build a clinical diagnostic model of primary open angle glaucoma （POAG） using the normal probability chart of frequency-domain optical coherence tomography （FD-OCT）. METHODS： This is a cross-sectional study. Total 133 eyes from 133 healthy subjects and 99 eyes from 99 early POAG patients were included in the study. The retinal nerve fibre layer （RNFL） thickness parameters of optic nerve head （ONH） and RNFL3.45 scan were measured in one randomly selected eye of each subject using RTVue-100 FD-OCT. Then, we used these parameters to establish the diagnostic models. Four different diagnostic models based on two different area partition strategies on ONH and RNFL3.45 parameters, including ONH traditional area partition model （ONH-T）, ONH new area partition model （ONH-N）, RNFL3.45 traditional area partition model （RNFL3.45-T） and RNFL3.45 new area partition model （RNFL3.45-N）, were built and tested by cross-validation. RESULTS： The new area partition models had higher area under the receiver operating characteristic （AROC; ONH-N： 0.990; RNFL3.45-N： 0.939） than corresponding traditional area partition models （ONH-T： 0.979; RNFL3.45-T： 0.881）. There was no statistical difference among AROC of ONH-T, ONH-N, and RNFL3.45-N. Nevertheless, ONH-N was the simplest model. CONCLUSION： The new area partition models had higher diagnostic accuracy than corresponding traditional area partition models, which can improve the diagnostic ability of early POAG. In particular, the simplest ONH-N diagnostic model may be convenient for clinical application.展开更多
In this article a new approach for checking the adequacy of GARCH-type models in time series was proposed. The resulted tests involve weight functions, which provide them with the flexibility in choosing scores to enh...In this article a new approach for checking the adequacy of GARCH-type models in time series was proposed. The resulted tests involve weight functions, which provide them with the flexibility in choosing scores to enhance power performance. The choice of weight functions and the power properties of the tests are studied. For a large number of alternatives, asymptotically distribution-free maximin test is constructed. The tests are asymptotically chi-squared under the null hypothesis and easy to implement. Simulation results indicate that the tests perform well.展开更多
The capacitively coupled radio frequency（CCRF）plasma has been widely used in various fields.In some cases,it requires us to estimate the range of key plasma parameters simpler and quicker in order to understand the ...The capacitively coupled radio frequency（CCRF）plasma has been widely used in various fields.In some cases,it requires us to estimate the range of key plasma parameters simpler and quicker in order to understand the behavior in plasma.In this paper,a glass vacuum chamber and a pair of plate electrodes were designed and fabricated,using 13.56 MHz radio frequency（RF）discharge technology to ionize the working gas of Ar.This discharge was mathematically described with equivalent circuit model.The discharge voltage and current of the plasma were measured atdifferent pressures and different powers.Based on the capacitively coupled homogeneous discharge model,the equivalent circuit and the analytical formula were established.The plasma density and temperature were calculated by using the equivalent impedance principle and energy balance equation.The experimental results show that when RF discharge power is 50–300 W and pressure is 25–250 Pa,the average electron temperature is about 1.7–2.1 e V and the average electron density is about 0.5？×10^17–3.6？×10^17m^-3.Agreement was found when the results were compared to those given by optical emission spectroscopy and COMSOL simulation.展开更多
Proper medical treatment of a stroke victim relies on accurate and rapid differentiation between ischemic and hemorrhagic stroke,which in current practice is performed by computerized tomography（CT） or magnetic reso...Proper medical treatment of a stroke victim relies on accurate and rapid differentiation between ischemic and hemorrhagic stroke,which in current practice is performed by computerized tomography（CT） or magnetic resonance imaging（MRI） scans.A panel of micro RNAs could be an extremely useful clinical tool for distinguishing between hemorrhagic and ischemic stroke.This review has shown that blood miRNA profile can distinguish hemorrhagic from ischemic stroke in patients and in experimental animal models.It also seems likely they can differentiate between intracerebral and subarachnoid hemorrhage stroke.The miRNA profile in cerebrospinal fluid could be a useful diagnostic tool for subarachnoid hemorrhagic stroke.Decreased or increased miRNA levels may be needed either as prevention or treatment of stroke.Administration in vivo of miR-130 a inhibitor or miRNA mimic（miR-367,miR-223） in an intracerebral hemorrhage animal model improved neurological outcomes.展开更多
<strong>Background: </strong>The significant improvement of immediate and long-term functional results of treating patients is the fundamental problem of modern medical science. A deep understanding of the...<strong>Background: </strong>The significant improvement of immediate and long-term functional results of treating patients is the fundamental problem of modern medical science. A deep understanding of the pathogenesis is the key point in creating the management strategy for patients with various diseases. Information about the mechanisms of origin and development of purulent-inflammatory diseases and sepsis is essential for finding effective ways to prevent and treat them. <strong>The aim of the research</strong> is to use the method of fluorescence spectroscopy in creating the pathogenetic diagnostic and treatment model for the prevention and treatment of purulent-inflammatory diseases and sepsis, modification of treatment tactics, search for new markers of purulent-septic diseases, as well as monitoring of patients during the treatment. <strong>Materials and methods: </strong>The proposed approach, along with standard diagnostic methods, was used to organize the treatment process of 100 patients with purulent-inflammatory diseases, including 15 patients with sepsis, 35 with acute inflammatory abdominal pathology, 20 patients with burn injury (main group) and 35 patients with burn injury (comparison group). <strong>Results:</strong> The behavior of spectral-fluorescent characteristics in their dynamics has been studied, and the new markers for assessing patients’ conditions have been proposed. Their effectiveness for the diagnosis of purulent-septic diseases has been proved, which advances the results of standard research methods by 24 - 48 hours.<strong> Conclusions:</strong> The proposed diagnostic and treatment approach is fundamentally important for diagnosis and monitoring during the treatment of patients with purulent-septic diseases. Particularly relevant is the proposal to modify the treatment process for these patients, associated with the use of infusion of donor albumin solutions.展开更多
In this paper,a tbree-dimensional (3-D) baroclinic diagnostic model for short-range numerical forecast is proposed to calculate the monthly averaged flow field in the Bohai Sea. By using the model and monthly averaged...In this paper,a tbree-dimensional (3-D) baroclinic diagnostic model for short-range numerical forecast is proposed to calculate the monthly averaged flow field in the Bohai Sea. By using the model and monthly averaged tempeature and salinity date, monthly barotropic and baroclinic flow field are calculated,and 2-D and 3-D characteristics of flow are described and demonstrated. On the basis of the analysis of the modelling results and the observed temperature,salinity and wind data,the monthly and seasonal characteristics and generation mechanism of circulation in the Bohai Sea are also discussed. It is pointed out in this paper that in spring and autumn,the monthly averaged flow fields are not representative, for the wind direction varies in a wide range and the averaged wind field is much weaker than the instantaneous one. These results show the reliability of the model for describing the monthly characteristics in numerical forecast of ocean current.展开更多
In paper it introduced a review of modem traction vehicle drive system with induction motor drive system （PMSM with single or dual rotor drive system） or BLDC motor with different configuration of magnetic circuits....In paper it introduced a review of modem traction vehicle drive system with induction motor drive system （PMSM with single or dual rotor drive system） or BLDC motor with different configuration of magnetic circuits. For particular part of drive system proposed a quasi intelligent control system version smart control enables multi criteria predictive control of vehicle work. In the paper presented also a selected diagnostic procedure, enables monitoring exploitation parameters, and prediction of probable failure state. For different vehicle work state realized a simulation models and crash test of exploitations failure models.展开更多
Background: The deep understanding of pathogenesis is a key moment in the formation of the modern strategy of modern medicine. We conducted the thorough analysis of the microscopic processes occurring in the bodies of...Background: The deep understanding of pathogenesis is a key moment in the formation of the modern strategy of modern medicine. We conducted the thorough analysis of the microscopic processes occurring in the bodies of patients with purulent-septic complications. The modified pathogenetic concept of the diagnostic and treatment model of diseases with septic complications is presented. The obtained information about the mechanisms of origin and development of these diseases is fundamentally important for finding the modern effective methods of treating patients. The aim of the research is to modify treatment tactics for patients with sepsis and burn injuries based on the modified pathogenetic concept using modern diagnostics, i.e. the method of fluorescence spectroscopy (MFS) and biomarkers. Materials and Methods: The proposed modified pathogenetic concept of the diagnostic and treatment model of diseases with purulent-septic complications along with standard methods was used successfully for effective treatment of 15 patients with sepsis and 25 with burn injuries. Results: 3 main scenarios of behaviour of spectral-fluorescence characteristics of patients with sepsis are illustrated. Spectral-fluorescence markers of sepsis were studied, which are informative 24 to 48 hours before the appearance of obvious clinical and laboratory signs of significant changes in the general somatic status of patients. Conclusions: The proposed diagnostic and therapeutic approach is new and fundamentally important for diagnostics and monitoring of the process of treatment of patients with purulent-septic diseases and burn injuries. An in-depth understanding of the dynamics of septic complications and the corresponding changes of the main markers of these diseases during treatment is especially relevant. The use of infusion therapy with solutions of donor albumin as an effective pathogenetic treatment is scientifically justified.展开更多
Objective A diagnostic model was established to discriminate infectious diseases from non-infectious diseases. Methods The clinical data of patients with fever of unknown origin(FUO) hospitalized in Xiangya Hospital C...Objective A diagnostic model was established to discriminate infectious diseases from non-infectious diseases. Methods The clinical data of patients with fever of unknown origin(FUO) hospitalized in Xiangya Hospital Central South University, from January, 2006 to April, 2011 were retrospectively analyzed. Patients enrolled were divided into two groups. The first group was used to develop a diagnostic model: independent variables were recorded and considered in a logistic regression analysis to identify infectious and non-infectious diseases(αin = 0.05, αout = 0.10). The second group was used to evaluate the diagnostic model and make ROC analysis.Results The diagnostic rate of 143 patients in the first group was 87.4%, the diagnosis included infectious disease(52.4%), connective tissue diseases(16.8%), neoplastic disease(16.1%) and miscellaneous(2.1%). The diagnostic rate of 168 patients in the second group was 88.4%, and the diagnosis was similar to the first group. Logistic regression analysis showed that decreased white blood cell count(WBC < 4.0×109/L), higher lactate dehydrogenase level(LDH > 320 U/L) and lymphadenectasis were independent risk factors associated with non-infectious diseases. The odds ratios were 14.74, 5.84 and 5.11(P ≤ 0.01), respectively. In ROC analysis, the sensitivity and specificity of the positive predictive values was 62.1% and 89.1%, respectively, while that of negative predicting values were 75% and 81.7%, respectively(AUC = 0.76, P = 0.00).Conclusions The combination of WBC < 4.0×109/L, LDH > 320 U/L and lymphadenectasis may be useful in discriminating infectious diseases from non-infectious diseases in patients hospitalized as FUO.展开更多
Vector of diagnostic signs(VDS)using torsional vibration(TV)signal on the main propulsion plant(MPP)is the vector of z maxima(or minima)values of the TV signal in accordance with the cylinder firing orders.The technic...Vector of diagnostic signs(VDS)using torsional vibration(TV)signal on the main propulsion plant(MPP)is the vector of z maxima(or minima)values of the TV signal in accordance with the cylinder firing orders.The technical states of the marine diesel engine(MDE)include R=z+1 classes and are presented in z-dimensional space coordinate of VDS.The presentation of Dk,k=1÷R using z diagnostic signs(Vi,i=1÷z)is nonfigurative and quite complicated.This paper aims to develop a new method for converting VDS from z-dimensional to 2-dimensional space(two-axes)based on the firing orders of the diesel cylinders,as an equivalent geometrical sign of the all diagnostic signs.The proposed model is useful for presenting a technical state Dk in two-dimensional space(x,y)for better visualization.The paper verifies the simulation of the classification illustration of the 7–state classes for the MDE 6S46-MCC,installed on the motor vessel(MV)34000DWT,using the new above mentioned method.The seven technical state classes(for 6-cylinder MDE,z=6)are drawn separately and visually in the Descartes.The received results are valuable to improve smart diagnostic system for analyzing normal/misfire states of cylinders in operation regimes.展开更多
文摘Mining rich semantic information hidden in heterogeneous information network is one of the important tasks of data mining. Generally, a nuclear medicine text consists of the description of disease (<i>i.e.</i>, lesions) and diagnostic results. However, how to construct a computer-aided diagnostic model with a large number of medical texts is a challenging task. To automatically diagnose diseases with SPECT imaging, in this work, we create a knowledge-based diagnostic model by exploring the association between a disease and its properties. Firstly, an overview of nuclear medicine and data mining is presented. Second, the method of preprocessing textual nuclear medicine diagnostic reports is proposed. Last, the created diagnostic modes based on random forest and SVM are proposed. Experimental evaluation conducted real-world data of diagnostic reports of SPECT imaging demonstrates that our diagnostic models are workable and effective to automatically identify diseases with textual diagnostic reports.
基金the Shanghai Municipal Key Clinical Specialty Program(No.shslczdzk06302)。
文摘Ovarian cancer has one of the highest mortality rates among gynecological malignancies.This disease has a low early detection rate,a high postoperative recurrence rate,and a 5-year survival rate of only 40%.Hence,there is an urgent need to improve the early diagnosis and prognosis of ovarian cancer.Prediction models can effectively estimate the risk of disease occurrence,as well as its prognosis.Recently,many studies have established multiple ovarian cancer prediction models based on different regions and populations.These models can improve the detection rate and optimize the prognosis management to a certain extent.Herein,the construction principle of the ovarian cancer risk prediction model and its validation are summarized;furthermore,comprehensive reviews and comparisons of the different types of these models are made.Therefore,our review may be of great significance for the whole course of ovarian cancer management.
基金financial support from the National Key R&D Program of China(Grant No.2020YFB1711100).
文摘To address the challenge of identifying the primary causes of energy consumption fluctuations and accurately assessing the influence of various factors in the converter unit of an iron and steel plant,the focus is placed on the critical components of material and heat balance.Through a thorough analysis of the interactions between various components and energy consumptions,six pivotal factors have been identified—raw material composition,steel type,steel temperature,slag temperature,recycling practices,and operational parameters.Utilizing a framework based on an equivalent energy consumption model,an integrated intelligent diagnostic model has been developed that encapsulates these factors,providing a comprehensive assessment tool for converter energy consumption.Employing the K-means clustering algorithm,historical operational data from the converter have been meticulously analyzed to determine baseline values for essential variables such as energy consumption and recovery rates.Building upon this data-driven foundation,an innovative online system for the intelligent diagnosis of converter energy consumption has been crafted and implemented,enhancing the precision and efficiency of energy management.Upon implementation with energy consumption data at a steel plant in 2023,the diagnostic analysis performed by the system exposed significant variations in energy usage across different converter units.The analysis revealed that the most significant factor influencing the variation in energy consumption for both furnaces was the steel grade,with contributions of−0.550 and 0.379.
基金supported by the Tencent Charity Foundationthe Ningxia Hui Autonomous Region Key Research and Development Program(No.2021BEG 02025)+1 种基金the Flexible Introduction of Technological Innovation Teams of Ningxia Hui Autonomous Region(No.2021RXTDLX15)the Natural Science Foundation of China(No.82160644)。
文摘Objective:A risk-based sequential screening strategy,from questionnaire-based assessment to biomarker measurement and then to endoscopic examination,has the potential to enhance gastric cancer(GC)screening efficiency.We aimed to evaluate the ability of five common stomach-specific serum biomarkers to further enrich high-risk individuals for GC in the questionnaire-identified high-risk population.Methods:This study was conducted based on a risk-based screening program in Ningxia Hui Autonomous Region,China.We first performed questionnaire assessment involving 23,381 individuals(7,042 outpatients and 16,339 individuals from the community),and those assessed as“high-risk”were then invited to participate in serological assays and endoscopic examinations.The serological biomarker model was derived based on logistic regression,with predictors selected via the Akaike information criterion.Model performance was evaluated by the area under the receiver operating characteristic curve(AUC).Results:A total of 2,011 participants were ultimately included for analysis.The final serological biomarker model had three predictors,comprising pepsinogenⅠ(PGI),pepsinogenⅠ/Ⅱratio(PGR),and anti-Helicobacter pylori immunoglobulin G(anti-H.pylori IgG)antibodies.This model generated an AUC of 0.733(95%confidence interval:0.655-0.812)and demonstrated the best discriminative ability compared with previously developed serological biomarker models.As the risk cut-off value of our model rose,the detection rate increased and the number of endoscopies needed to detect one case decreased.Conclusions:PGI,PGR,and anti-H.pylori Ig G could be jointly used to further enrich high-risk individuals for GC among those selected by questionnaire assessment,providing insight for the development of a multi-stage riskbased sequential strategy for GC screening.
基金supported by the Project Funding of the Fund Committee of Science Department (No.40346029)National Natural Science Foundation (40346029)the offing comprehensive evaluation of our country (908-02-01-03)
文摘A 2-dimensional global free surface diagnostic model, combined with dynamic calculation, is used to investigate the world ocean circulation; the model has a horizontal resolution of 1/4°×1/4°. The simulated results agree well with the results of other modesl and observations. The distribution of Stream Function suggests that the main circulation systems in the wodd ocean have been represented, including oceanic currents strengthened in the oceanic western. Be close to the observed results, the net mass transport of the Kuroshio axes is estimated about 54Sv; The distribution of the horizontal circulation in each layer shows that the main circulation systems in the world ocean are well simulated, for example, the Kuroshio and the Antarctic Circumpolar Current can go down to the bottom layer, but the Gulf Stream cannot, and its direction reverses at the depths of 1000 to 2 000 m.
基金supported by the Capital Medical Development and Scientific Research Fund(2009-1033)and the Science and Technology Plan of Beijing City(Z101107050210018)
文摘We established a diagnostic model to predict acute Mycoplasma pneumoniae （M. pneumonia） infection in elderly Community-acquired pneumonia （CAP） patients. We divided 456 patients into acute and non-acute M. pneumoniae infection groups. Binary logistic regression and receiver operating characteristic （ROC） curves were used to establish a predictive model. The following independent factors were identified： age 〉 70 years; serum cTNT level 〉 0.0S ng/mL; lobar consolidation; mediastinal lymphadenopathy; and antibody titer in the acute phase 〉 1：40. The area under the ROC curve of the model was 0.923 and a score of 2 7 score predicted acute M. pneumoniae infection in elderly patients with CAP. The predictive model developed in this study has high diagnostic accuracy for the identification of elderly acute M. pneumoniae infection.
基金Chinese Academy of Sciences under contract No.KZCX2-YW-214the National Nat-ural Science Foundation of China under contract Nos 40476014 and 40346029.
文摘A high resolved two-dimensional linear global diagnostic model combining with the dynamical calculation is used to calculate velocity field in the South China Sea(SCS). The study of model results shows that eddy diffusion does not change basic structure of circulation in the SCS and does not change the direction of invasive water, but changes the value of transport considerably especially in straits. The velocity field is not changed whether the wind stress is considered or not. This result shows the circulation is largely determined by a density field which well records most of the important contribution of the wind stress effect. Potential vorticity is calculated to testify the dynamics of the model results. The result shows that a good conservation of the nonlinear PV. This indicates most effects of the important nonlinear processes are well recorded in density and the nonlinear term is negligible so that the simplified model is reliable. The model results show the water exchanges between the SCS and open ocean or surrounding seas. Cold deep water invades through Luzon Strait and Warm shallow water is pushed out mainly through Karimata Straits. The model results also reveal the structure of the circulation in the SCS basin. In two circulations of upper and middle layers, a cyclonic one in the north and an anti-cyclonic one in the south, reflect the climatologic average of the circulation driven by monsoon. In the deep or bottom layer, these two circulations reflect the topography of the basin. Above the middle layer, invasive water enters westward in the north but the way of invasion of Kuroshio is not clear. Below the deep layer, a current goes down south near the east basin ,and invasive water enters in the basin from the west Pacific.
基金Supported by the Medical and Health Research Project of Zhejiang Province,No.2021KY1048 and 2022KY1142Ningbo Health Young Technical Backbone Talents Training Program,No.2020SWSQNGG-02the Key Science and Technology Project of Ningbo City,No.2021Z133.
文摘BACKGROUND Colorectal cancer(CRC)is a major global health burden.The current diagnostic tests have shortcomings of being invasive and low accuracy.AIM To explore the combination of intestinal microbiome composition and multi-target stool DNA(MT-sDNA)test in the diagnosis of CRC.METHODS We assessed the performance of the MT-sDNA test based on a hospital clinical trial.The intestinal microbiota was tested using 16S rRNA gene sequencing.This case-control study enrolled 54 CRC patients and 51 healthy controls.We identified biomarkers of bacterial structure,analyzed the relationship between different tumor markers and the relative abundance of related flora components,and distinguished CRC patients from healthy subjects by the linear discriminant analysis effect size,redundancy analysis,and random forest analysis.RESULTS MT-sDNA was associated with Bacteroides.MT-sDNA and carcinoembryonic antigen(CEA)were positively correlated with the existence of Parabacteroides,and alpha-fetoprotein(AFP)was positively associated with Faecalibacterium and Megamonas.In the random forest model,the existence of Streptococcus,Escherichia,Chitinophaga,Parasutterella,Lachnospira,and Romboutsia can distinguish CRC from health controls.The diagnostic accuracy of MT-sDNA combined with the six genera and CEA in the diagnosis of CRC was 97.1%,with a sensitivity and specificity of 98.1%and 92.3%,respectively.CONCLUSION There is a positive correlation of MT-sDNA,CEA,and AFP with intestinal microbiome.Eight biomarkers including six genera of gut microbiota,MT-sDNA,and CEA showed a prominent sensitivity and specificity for CRC prediction,which could be used as a non-invasive method for improving the diagnostic accuracy for this malignancy.
基金Supported by the Projects of Public Science and Technology Research Funds of Ocean Sector of China(No.201205009)the National Natural Science Foundation of China(No.41201569)
文摘Presently, research is lacking regarding the diagnosis and evaluation of habitat degradation in enclosed bay systems. We established a diagnostic model for enclosed bay habitat degradation(EBHD model) using a multi-approach integrated diagnostic method in consideration of driving force-pressurestate-infl uence-response. The model optimizes the indicator standardization with annual average change rate of habitat degradation as the basic element, to refl ect accurately the impact of the change and speed of degradation on the diagnostic results, to quantify reasonably the contribution of individual diagnostic indicator to habitat degradation, and to solve the issue regarding the infl uence of subjective factors on the evaluation results during indicator scoring. We then applied the EBHD model for the Sansha Bay in Fujian Province, China, evaluated comprehensively the situation of habitat degradation in the bay, and screened out the major controlling factors in the study area. Results show that the diagnostic results are consistent in overall with the real situation of the study area. Therefore, the EBHD model is advantageous in terms of objectivity and accuracy, making a breakthrough in diagnosis and evaluation for habitat degradation in enclosed bay systems.
基金the National Natural Science Foundation of China(Grant Number:81970631 to W.L.).
文摘Background:Diabetic nephropathy(DN)is the most common complication of type 2 diabetes mellitus and the main cause of end-stage renal disease worldwide.Diagnostic biomarkers may allow early diagnosis and treatment of DN to reduce the prevalence and delay the development of DN.Kidney biopsy is the gold standard for diagnosing DN;however,its invasive character is its primary limitation.The machine learning approach provides a non-invasive and specific criterion for diagnosing DN,although traditional machine learning algorithms need to be improved to enhance diagnostic performance.Methods:We applied high-throughput RNA sequencing to obtain the genes related to DN tubular tissues and normal tubular tissues of mice.Then machine learning algorithms,random forest,LASSO logistic regression,and principal component analysis were used to identify key genes(CES1G,CYP4A14,NDUFA4,ABCC4,ACE).Then,the genetic algorithm-optimized backpropagation neural network(GA-BPNN)was used to improve the DN diagnostic model.Results:The AUC value of the GA-BPNN model in the training dataset was 0.83,and the AUC value of the model in the validation dataset was 0.81,while the AUC values of the SVM model in the training dataset and external validation dataset were 0.756 and 0.650,respectively.Thus,this GA-BPNN gave better values than the traditional SVM model.This diagnosis model may aim for personalized diagnosis and treatment of patients with DN.Immunohistochemical staining further confirmed that the tissue and cell expression of NADH dehydrogenase(ubiquinone)1 alpha subcomplex,4-like 2(NDUFA4L2)in tubular tissue in DN mice were decreased.Conclusion:The GA-BPNN model has better accuracy than the traditional SVM model and may provide an effective tool for diagnosing DN.
文摘AIM： To build a clinical diagnostic model of primary open angle glaucoma （POAG） using the normal probability chart of frequency-domain optical coherence tomography （FD-OCT）. METHODS： This is a cross-sectional study. Total 133 eyes from 133 healthy subjects and 99 eyes from 99 early POAG patients were included in the study. The retinal nerve fibre layer （RNFL） thickness parameters of optic nerve head （ONH） and RNFL3.45 scan were measured in one randomly selected eye of each subject using RTVue-100 FD-OCT. Then, we used these parameters to establish the diagnostic models. Four different diagnostic models based on two different area partition strategies on ONH and RNFL3.45 parameters, including ONH traditional area partition model （ONH-T）, ONH new area partition model （ONH-N）, RNFL3.45 traditional area partition model （RNFL3.45-T） and RNFL3.45 new area partition model （RNFL3.45-N）, were built and tested by cross-validation. RESULTS： The new area partition models had higher area under the receiver operating characteristic （AROC; ONH-N： 0.990; RNFL3.45-N： 0.939） than corresponding traditional area partition models （ONH-T： 0.979; RNFL3.45-T： 0.881）. There was no statistical difference among AROC of ONH-T, ONH-N, and RNFL3.45-N. Nevertheless, ONH-N was the simplest model. CONCLUSION： The new area partition models had higher diagnostic accuracy than corresponding traditional area partition models, which can improve the diagnostic ability of early POAG. In particular, the simplest ONH-N diagnostic model may be convenient for clinical application.
基金supported by a grant from the Research Grants Council of Hong Kong.Jianhong Wu was also supported by a grant from Humanities & Social Sciences in Chinese University (07JJD790154)the Youth Talent Foundation of Zhejiang GongShang University (Q09-12)
文摘In this article a new approach for checking the adequacy of GARCH-type models in time series was proposed. The resulted tests involve weight functions, which provide them with the flexibility in choosing scores to enhance power performance. The choice of weight functions and the power properties of the tests are studied. For a large number of alternatives, asymptotically distribution-free maximin test is constructed. The tests are asymptotically chi-squared under the null hypothesis and easy to implement. Simulation results indicate that the tests perform well.
基金supported by National Natural Science Foundation of China(Grant No.61378037)the Fundamental Research Funds for the Central Universities(Nos.2013B33614,2017B15214)+1 种基金the Research Funds of Innovation and Entrepreneurship Education Reform for Chinese Universities(No.16CCJG01Z004)the Changzhou Science and Technology Program(No.CJ20160027)
文摘The capacitively coupled radio frequency（CCRF）plasma has been widely used in various fields.In some cases,it requires us to estimate the range of key plasma parameters simpler and quicker in order to understand the behavior in plasma.In this paper,a glass vacuum chamber and a pair of plate electrodes were designed and fabricated,using 13.56 MHz radio frequency（RF）discharge technology to ionize the working gas of Ar.This discharge was mathematically described with equivalent circuit model.The discharge voltage and current of the plasma were measured atdifferent pressures and different powers.Based on the capacitively coupled homogeneous discharge model,the equivalent circuit and the analytical formula were established.The plasma density and temperature were calculated by using the equivalent impedance principle and energy balance equation.The experimental results show that when RF discharge power is 50–300 W and pressure is 25–250 Pa,the average electron temperature is about 1.7–2.1 e V and the average electron density is about 0.5？×10^17–3.6？×10^17m^-3.Agreement was found when the results were compared to those given by optical emission spectroscopy and COMSOL simulation.
文摘Proper medical treatment of a stroke victim relies on accurate and rapid differentiation between ischemic and hemorrhagic stroke,which in current practice is performed by computerized tomography（CT） or magnetic resonance imaging（MRI） scans.A panel of micro RNAs could be an extremely useful clinical tool for distinguishing between hemorrhagic and ischemic stroke.This review has shown that blood miRNA profile can distinguish hemorrhagic from ischemic stroke in patients and in experimental animal models.It also seems likely they can differentiate between intracerebral and subarachnoid hemorrhage stroke.The miRNA profile in cerebrospinal fluid could be a useful diagnostic tool for subarachnoid hemorrhagic stroke.Decreased or increased miRNA levels may be needed either as prevention or treatment of stroke.Administration in vivo of miR-130 a inhibitor or miRNA mimic（miR-367,miR-223） in an intracerebral hemorrhage animal model improved neurological outcomes.
文摘<strong>Background: </strong>The significant improvement of immediate and long-term functional results of treating patients is the fundamental problem of modern medical science. A deep understanding of the pathogenesis is the key point in creating the management strategy for patients with various diseases. Information about the mechanisms of origin and development of purulent-inflammatory diseases and sepsis is essential for finding effective ways to prevent and treat them. <strong>The aim of the research</strong> is to use the method of fluorescence spectroscopy in creating the pathogenetic diagnostic and treatment model for the prevention and treatment of purulent-inflammatory diseases and sepsis, modification of treatment tactics, search for new markers of purulent-septic diseases, as well as monitoring of patients during the treatment. <strong>Materials and methods: </strong>The proposed approach, along with standard diagnostic methods, was used to organize the treatment process of 100 patients with purulent-inflammatory diseases, including 15 patients with sepsis, 35 with acute inflammatory abdominal pathology, 20 patients with burn injury (main group) and 35 patients with burn injury (comparison group). <strong>Results:</strong> The behavior of spectral-fluorescent characteristics in their dynamics has been studied, and the new markers for assessing patients’ conditions have been proposed. Their effectiveness for the diagnosis of purulent-septic diseases has been proved, which advances the results of standard research methods by 24 - 48 hours.<strong> Conclusions:</strong> The proposed diagnostic and treatment approach is fundamentally important for diagnosis and monitoring during the treatment of patients with purulent-septic diseases. Particularly relevant is the proposal to modify the treatment process for these patients, associated with the use of infusion of donor albumin solutions.
文摘In this paper,a tbree-dimensional (3-D) baroclinic diagnostic model for short-range numerical forecast is proposed to calculate the monthly averaged flow field in the Bohai Sea. By using the model and monthly averaged tempeature and salinity date, monthly barotropic and baroclinic flow field are calculated,and 2-D and 3-D characteristics of flow are described and demonstrated. On the basis of the analysis of the modelling results and the observed temperature,salinity and wind data,the monthly and seasonal characteristics and generation mechanism of circulation in the Bohai Sea are also discussed. It is pointed out in this paper that in spring and autumn,the monthly averaged flow fields are not representative, for the wind direction varies in a wide range and the averaged wind field is much weaker than the instantaneous one. These results show the reliability of the model for describing the monthly characteristics in numerical forecast of ocean current.
文摘In paper it introduced a review of modem traction vehicle drive system with induction motor drive system （PMSM with single or dual rotor drive system） or BLDC motor with different configuration of magnetic circuits. For particular part of drive system proposed a quasi intelligent control system version smart control enables multi criteria predictive control of vehicle work. In the paper presented also a selected diagnostic procedure, enables monitoring exploitation parameters, and prediction of probable failure state. For different vehicle work state realized a simulation models and crash test of exploitations failure models.
文摘Background: The deep understanding of pathogenesis is a key moment in the formation of the modern strategy of modern medicine. We conducted the thorough analysis of the microscopic processes occurring in the bodies of patients with purulent-septic complications. The modified pathogenetic concept of the diagnostic and treatment model of diseases with septic complications is presented. The obtained information about the mechanisms of origin and development of these diseases is fundamentally important for finding the modern effective methods of treating patients. The aim of the research is to modify treatment tactics for patients with sepsis and burn injuries based on the modified pathogenetic concept using modern diagnostics, i.e. the method of fluorescence spectroscopy (MFS) and biomarkers. Materials and Methods: The proposed modified pathogenetic concept of the diagnostic and treatment model of diseases with purulent-septic complications along with standard methods was used successfully for effective treatment of 15 patients with sepsis and 25 with burn injuries. Results: 3 main scenarios of behaviour of spectral-fluorescence characteristics of patients with sepsis are illustrated. Spectral-fluorescence markers of sepsis were studied, which are informative 24 to 48 hours before the appearance of obvious clinical and laboratory signs of significant changes in the general somatic status of patients. Conclusions: The proposed diagnostic and therapeutic approach is new and fundamentally important for diagnostics and monitoring of the process of treatment of patients with purulent-septic diseases and burn injuries. An in-depth understanding of the dynamics of septic complications and the corresponding changes of the main markers of these diseases during treatment is especially relevant. The use of infusion therapy with solutions of donor albumin as an effective pathogenetic treatment is scientifically justified.
文摘Objective A diagnostic model was established to discriminate infectious diseases from non-infectious diseases. Methods The clinical data of patients with fever of unknown origin(FUO) hospitalized in Xiangya Hospital Central South University, from January, 2006 to April, 2011 were retrospectively analyzed. Patients enrolled were divided into two groups. The first group was used to develop a diagnostic model: independent variables were recorded and considered in a logistic regression analysis to identify infectious and non-infectious diseases(αin = 0.05, αout = 0.10). The second group was used to evaluate the diagnostic model and make ROC analysis.Results The diagnostic rate of 143 patients in the first group was 87.4%, the diagnosis included infectious disease(52.4%), connective tissue diseases(16.8%), neoplastic disease(16.1%) and miscellaneous(2.1%). The diagnostic rate of 168 patients in the second group was 88.4%, and the diagnosis was similar to the first group. Logistic regression analysis showed that decreased white blood cell count(WBC < 4.0×109/L), higher lactate dehydrogenase level(LDH > 320 U/L) and lymphadenectasis were independent risk factors associated with non-infectious diseases. The odds ratios were 14.74, 5.84 and 5.11(P ≤ 0.01), respectively. In ROC analysis, the sensitivity and specificity of the positive predictive values was 62.1% and 89.1%, respectively, while that of negative predicting values were 75% and 81.7%, respectively(AUC = 0.76, P = 0.00).Conclusions The combination of WBC < 4.0×109/L, LDH > 320 U/L and lymphadenectasis may be useful in discriminating infectious diseases from non-infectious diseases in patients hospitalized as FUO.
文摘Vector of diagnostic signs(VDS)using torsional vibration(TV)signal on the main propulsion plant(MPP)is the vector of z maxima(or minima)values of the TV signal in accordance with the cylinder firing orders.The technical states of the marine diesel engine(MDE)include R=z+1 classes and are presented in z-dimensional space coordinate of VDS.The presentation of Dk,k=1÷R using z diagnostic signs(Vi,i=1÷z)is nonfigurative and quite complicated.This paper aims to develop a new method for converting VDS from z-dimensional to 2-dimensional space(two-axes)based on the firing orders of the diesel cylinders,as an equivalent geometrical sign of the all diagnostic signs.The proposed model is useful for presenting a technical state Dk in two-dimensional space(x,y)for better visualization.The paper verifies the simulation of the classification illustration of the 7–state classes for the MDE 6S46-MCC,installed on the motor vessel(MV)34000DWT,using the new above mentioned method.The seven technical state classes(for 6-cylinder MDE,z=6)are drawn separately and visually in the Descartes.The received results are valuable to improve smart diagnostic system for analyzing normal/misfire states of cylinders in operation regimes.
