Traditional Chinese medicine(TCM)represents a paradigmatic approach to personalized medicine,developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years,and now en...Traditional Chinese medicine(TCM)represents a paradigmatic approach to personalized medicine,developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years,and now encompasses large-scale electronic medical records(EMR)and experimental molecular data.Artificial intelligence(AI)has demonstrated its utility in medicine through the development of various expert systems(e.g.,MYCIN)since the 1970s.With the emergence of deep learning and large language models(LLMs),AI’s potential in medicine shows considerable promise.Consequently,the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction.This survey provides an insightful overview of TCM AI research,summarizing related research tasks from three perspectives:systems-level biological mechanism elucidation,real-world clinical evidence inference,and personalized clinical decision support.The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice.To critically assess the current state of the field,this work identifies major challenges and opportunities that constrain the development of robust research capabilities—particularly in the mechanistic understanding of TCM syndromes and herbal formulations,novel drug discovery,and the delivery of high-quality,patient-centered clinical care.The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality,large-scale data repositories;the construction of comprehensive and domain-specific knowledge graphs(KGs);deeper insights into the biological mechanisms underpinning clinical efficacy;rigorous causal inference frameworks;and intelligent,personalized decision support systems.展开更多
Decision Support Tool(DST)enables farmers to make site-specific crop management decisions;however,comprehensive calibration can be both costly and time-consuming.This study assessed the production and economic benefit...Decision Support Tool(DST)enables farmers to make site-specific crop management decisions;however,comprehensive calibration can be both costly and time-consuming.This study assessed the production and economic benefits of two calibrations of the Nutrient Expert(NE)tool for rice in Sri Lanka’s Alfisols:the basic calibration(Nutrient Expert Sri Lanka 1,NESL1)and the comprehensive calibration(Nutrient Expert Sri Lanka 2,NESL2).NESL1 was developed by adapting the South Indian version of NE to local conditions,while NESL2 was an updated version,using three years of data from 71 farmer fields.展开更多
BACKGROUND Cancer care faces challenges due to tumor heterogeneity and rapidly evolving therapies,necessitating artificial intelligence(AI)-driven clinical decision support.While general-purpose models like ChatGPT of...BACKGROUND Cancer care faces challenges due to tumor heterogeneity and rapidly evolving therapies,necessitating artificial intelligence(AI)-driven clinical decision support.While general-purpose models like ChatGPT offer adaptability,domain-specific systems(e.g.,DeepSeek)may better align with clinical guidelines.However,their comparative efficacy in oncology remains underexplored.This study hypothesizes that domain-specific AI will outperform general-purpose models in technical accuracy,while the latter will excel in patient-centered communication.AIMS To compare ChatGPT and DeepSeek in oncology decision support for diagnosis,treatment,and patient communication.METHODS A retrospective analysis was conducted using 1200 anonymized oncology cases(2018–2023)from The Cancer Genome Atlas and institutional databases,covering six cancer types.Each case included histopathology,imaging,genomic profiles,and treatment histories.Both models generated diagnostic interpretations,staging assessments,and therapy recommendations.Performance was evaluated against NCCN/ESMO guidelines and expert oncologist panels using F1-scores,Cohen'sκ,Likert-scale ratings,and readability metrics.Statistical significance was assessed via analysis of variance and post-hoc Tukey tests.RESULTS DeepSeek demonstrated superior performance in diagnostic accuracy(F1-score:89.2%vs ChatGPT's 76.5%,P<0.001)and treatment alignment with guidelines(κ=0.82 vs 0.67,P=0.003).ChatGPT exhibited strengths in patient communi-cation,generating layman-friendly explanations(readability score:8.2/10 vs DeepSeek's 6.5/10,P=0.012).Both models showed limitations in rare cancer subtypes(e.g.,cholangiocarcinoma),with accuracy dropping below 60%.Clinicians rated DeepSeek's outputs as more actionable(4.3/5 vs 3.7/5,P=0.021)but highlighted ChatGPT's utility in palliative care discussions.CONCLUSION Domain-specific AI(DeepSeek)excels in technical precision,while general-purpose models(ChatGPT)enhance patient engagement.A hybrid system integrating both approaches may optimize oncology workflows,contingent on expanded training for rare cancers and real-time guideline updates.展开更多
Artificial intelligence(AI)is rapidly transforming radiology and computed tomography(CT)imaging by enabling automated image analysis,improved diagnostic accuracy,and clinical decision-support.We performed a systematic...Artificial intelligence(AI)is rapidly transforming radiology and computed tomography(CT)imaging by enabling automated image analysis,improved diagnostic accuracy,and clinical decision-support.We performed a systematic review of peerreviewed studies published between January 1,2010 and March 31,2025 to quantify reported gains in diagnostic performance and workflow efficiency,to evaluate clinical decision-support benefits and risks,and to identify integration priorities.We searched PubMed,IEEE Xplore,Scopus,ScienceDirect,and Google Scholar and screened 128 records;26 studies met the inclusion criteria.Extracted data included study design,AI architecture,sample size,and quantitative performance metrics;study quality was assessed using Newcastle-Ottawa Scales(NOS),Cochrane RoB 2,or AMSTAR 2 as appropriate.Across included studies,AI applications in CT showed consistent improvements in sensitivity,specificity,and time-to-diagnosis in specific tasks(notably lung-nodule detection and intracranial hemorrhage triage),with reported detection-rate increases up to~20%and reduced turnaround times in several real-world implementations.Barriers include dataset bias,limited external validation,interpretability(“black-box”)concerns,workflow integration challenges,and evolving regulatory issues.Economic analyses suggest potentially favorable return on investment(ROI)in high-volume settings but are sensitive to licensing and infrastructure costs.To realize AI's benefits in CT imaging,rigorous multi-center validation,transparent reporting,humancentered workflow design,and post-deployment surveillance are essential.展开更多
Background: Clinical decision support tools provide suggestions to support healthcare providers and clinicians, as they attend to patients. Clinicians use these tools to rapidly consult the evidence at the point of ca...Background: Clinical decision support tools provide suggestions to support healthcare providers and clinicians, as they attend to patients. Clinicians use these tools to rapidly consult the evidence at the point of care, a practice which has been found to reduce the time patients spend in hospitals, promote the quality of care and improve healthcare outcomes. Such tools include Medscape, VisualDx, Clinical Key, DynaMed, BMJ Best Practice and UpToDate. However, use of such tools has not yet been fully embraced in low-resource settings such as Uganda. Objective: This paper intends to collate data on the use and uptake of one such tool, UpToDate, which was provided at no cost to five medical schools in Uganda. Methods: Free access to UpToDate was granted through the IP addresses of five medical schools in Uganda in collaboration with Better Evidence at The Global Health Delivery Project at Harvard and Brigham and Women’s Hospital and Wolters Kluwer Health. Following the donation, medical librarians in the respective institutions conducted training sessions and created awareness of the tool. Usage data was aggregated, based on logins and content views, presented and analyzed using Excel tables and graphs. Results: The data shows similar trends in increased usage over the period of August 2022 to August 2023 across the five medical schools. The most common topics viewed, mode of access (using either the computer or the mobile app), total usage by institution, ratio of uses to eligible users by institution and ratio of uses to students by institution are shared. Conclusion: The study revealed that the tool was used by various user categories across the institutions with similar steady improved usage over the year. These results can inform the librarians as they encourage their respective institutions to continue using the tool to support uptake of point-of-care tools in clinical practice.展开更多
This study presents an AI-driven Spatial Decision Support System (SDSS) aimed at transforming groundwater suitability assessments for domestic and irrigation uses in Visakhapatnam District, Andhra Pradesh, India. By e...This study presents an AI-driven Spatial Decision Support System (SDSS) aimed at transforming groundwater suitability assessments for domestic and irrigation uses in Visakhapatnam District, Andhra Pradesh, India. By employing advanced remote sensing, GIS, and machine learning techniques, groundwater quality data from 50 monitoring wells, sourced from the Central Ground Water Board (CGWB), was meticulously analysed. Key parameters, including pH, electrical conductivity, total dissolved solids, and major ion concentrations, were evaluated against World Health Organization (WHO) standards to determine domestic suitability. For irrigation, advanced metrics such as Sodium Adsorption Ratio (SAR), Kelly’s Ratio, Residual Sodium Carbonate (RSC), and percentage sodium (% Na) were utilized to assess water quality. The integration of GIS for spatial mapping and AI models for predictive analytics allows for a comprehensive visualization of groundwater quality distribution across the district. Additionally, the irrigation water quality was evaluated using the USA Salinity Laboratory diagram, providing essential insights for effective agricultural water management. This innovative SDSS framework promises to significantly enhance groundwater resource management, fostering sustainable practices for both domestic use and agriculture in the region.展开更多
Decision support systems(DSS)based on physically based numerical models are standard tools used by water services and utilities.However,few DSS based on holistic approaches combining distributed hydrological,hydraulic...Decision support systems(DSS)based on physically based numerical models are standard tools used by water services and utilities.However,few DSS based on holistic approaches combining distributed hydrological,hydraulic,and hydrogeological models are operationally exploited.This holistic approach was adopted for the development of the AquaVar DSS,used for water resource management in the French Mediterranean Var watershed.The year 2019 marked the initial use of the DSS in its operational environment.Over the next 5 years,multiple hydrological events allowed to test the performance of the DSS.The results show that the tool is capable of simulating peak flows associated with two extreme rainfall events(storms Alex and Aline).For a moderate flood,the real-time functionality was able to simulate forecast discharges 26 h before the flood peak,with a maximum local error of 30%.Finally,simulations for the drought period 2022-2023 highlighted the essential need for DSS to evolve in line with changing climatic conditions,which give rise to unprecedented hydrological processes.The lessons learned from these first 5 years of AquaVar use under operational conditions are synthesized,addressing various topics such as DSS modularity,evolution,data positioning,technology,and governance.展开更多
In order to solve existing problems about the method of establishing traditional system structure of decision support system(DSS), O S chart is applied to describe object oriented system structure of general DSS, an...In order to solve existing problems about the method of establishing traditional system structure of decision support system(DSS), O S chart is applied to describe object oriented system structure of general DSS, and a new method of eight specific steps is proposed to establish object oriented system structure of DSS by using the method of O S chart, which is applied successfully to the development of the DSS for the energy system ecology engineering research of the Wangheqiu country. Supplying many scientific effective computing models, decision support ways and a lot of accurate reliable decision data, the DSS plays a critical part in helping engineering researchers to make correct decisions. Because the period for developing the DSS is relatively shorter, the new way improves the efficiency of establishing DSS greatly. It also makes the DSS of system structure more flexible and easy to expand.展开更多
In order to solve the problem of the maze precision fertilizer,soil fertility evaluation,soil fertility classify and yield projections,the geographic information system with spatial information processing functions,sp...In order to solve the problem of the maze precision fertilizer,soil fertility evaluation,soil fertility classify and yield projections,the geographic information system with spatial information processing functions,spatial data mining techniques with spatial information analysis capabilities,expert system technology in the field of artificial intelligence,traditional information management systems and decision support system were effectively integrated in this study,and the statistical analysis method of GIS and data visualization were combined to design and implement the maize precise intelligent space decision-making system.This system had greatly improved the decision-making ability in agricultural production carried out by agricultural management.展开更多
[Objective] This study was to provide methods to improve the scientificity and informatization level of agricultural decision-making system based on the study of Decision Support System for ＂Northing of Winter Wheat...[Objective] This study was to provide methods to improve the scientificity and informatization level of agricultural decision-making system based on the study of Decision Support System for ＂Northing of Winter Wheat＂ in Hebei Province （DSS- NWWH）. [Method] The functions, development process, operation guidance as well as input and output modes of DSSNWWH were introduced, and the simulated results of the system were verified by comparing with the actual situations. [Result] The decision support system established in this study could predict whether a wheat variety could live through the winter in a certain area of northern Hebei Province, as well as the growth conditions based on the previous meteorological data or local weather forecast, and provided corresponding cultivation and management measures, making it possible for the user to determine whether the variety could be planted in the region based on the predictions. [Conclusion] The established DSSNWWH in this study can effectively help decision makers make decisions, providing scientific instructions for the northing of winter wheat.展开更多
The objectives of this study are to assess land s ui tability and to predict the spatial and temporal changes in land use types (LUTs ) by using GIS-based land use management decision support system. A GIS databas e w...The objectives of this study are to assess land s ui tability and to predict the spatial and temporal changes in land use types (LUTs ) by using GIS-based land use management decision support system. A GIS databas e with data on climate, topography, soil characteristic, irrigation condition, f ertilizer application, and special socioeconomic activities has been developed a nd used for the evaluation of land productivity for different crops by integrati ng with a crop growth model-the erosion productivity impact calculator (EPIC). International food policy simulation model (IFPSIM) is also embedded into GIS fo r the predictions of how crop demands and crop market prices will change under a lternative policy scenarios. An inference engine (IE) including land use choice model is developed to illustrate land use choice behavior based on logit models , which allows to analyze how diversified factors ranging from climate changes, crop price changes to land management changes can affect the distribution of agr icultural land use. A test for integrated simulation is taken in each 0.1° by 0.1° grid cell to predict the change of agricultural land use types at globa l level. Global land use changes are simulated from 1992 to 2050.展开更多
Ballistic missile defense system (BMDS) is important for its special role in ensuring national security and maintaining strategic balance. Research on modeling and simulation of the BMDS beforehand is essential as dev...Ballistic missile defense system (BMDS) is important for its special role in ensuring national security and maintaining strategic balance. Research on modeling and simulation of the BMDS beforehand is essential as developing a real one requires lots of manpower and resources. BMDS is a typical complex system for its nonlinear, adaptive and uncertainty characteristics. The agent-based modeling method is well suited for the complex system whose overall behaviors are determined by interactions among individual elements. A multi-agent decision support system (DSS), which includes missile agent, radar agent and command center agent, is established based on the studies of structure and function of BMDS. Considering the constraints brought by radar, intercept missile, offensive missile and commander, the objective function of DSS is established. In order to dynamically generate the optimal interception plan, the variable neighborhood negative selection particle swarm optimization (VNNSPSO) algorithm is proposed to support the decision making of DSS. The proposed algorithm is compared with the standard PSO, constriction factor PSO (CFPSO), inertia weight linear decrease PSO (LDPSO), variable neighborhood PSO (VNPSO) algorithm from the aspects of convergence rate, iteration number, average fitness value and standard deviation. The simulation results verify the efficiency of the proposed algorithm. The multi-agent DSS is developed through the Repast simulation platform and the constructed DSS can generate intercept plans automatically and support three-dimensional dynamic display of missile defense process.展开更多
Forest ecosystems are our priceless natural resource and are a key component of the global carbon budget. Forest fires can be a hazard to the viability and sustainable management of forests with consequences for natur...Forest ecosystems are our priceless natural resource and are a key component of the global carbon budget. Forest fires can be a hazard to the viability and sustainable management of forests with consequences for natural and cultural environments, economies, and the life quality of local and regional populations. Thus, the selection of strategies to manage forest fires, while considering both functional and economic efficiency, is of primary importance. The use of decision support systems(DSSs) by managers of forest fires has rapidly increased. This has strengthened capacity to prevent and suppress forest fires while protecting human lives and property. DSSs are a tool that can benefit incident management and decision making and policy, especially for emergencies such as natural disasters. In this study we reviewed state-of-the-art DSSs that use: database management systems and mathematical/economic algorithms for spatial optimization of firefighting forces; forest fire simulators and satellite technology for immediate detection and prediction of evolution of forest fires; GIS platforms that incorporate several tools to manipulate, process and analyze geographic data and develop strategic and operational plans.展开更多
It is important and difficult to control the temperature of mass concrete structure during high arch dam construction.A new method with decision support system is presented for temperature control and crack prevention...It is important and difficult to control the temperature of mass concrete structure during high arch dam construction.A new method with decision support system is presented for temperature control and crack prevention.It is a database system with functions of data storage,information inquiry,data analysis,early warning and resource sharing.Monitoring information during construction can be digitized via this system,and the intelligent analysis and dynamic control of concrete temperature can be conducted.This method has been applied in the construction of the Dagangshan Arch Dam in China and has proven to be very convenient.Based on the decision support of this system and the dynamic adjustment of construction measures,the concrete temperature of this project is well-controlled.展开更多
Highways in mountainous areas are easy to be damaged by such natural disasters as debris flows and landslides and disaster reduction decision support system (DRDSS) is one of the important means to mitigate these disa...Highways in mountainous areas are easy to be damaged by such natural disasters as debris flows and landslides and disaster reduction decision support system (DRDSS) is one of the important means to mitigate these disasters. Guided by the theories and technologies of debris flow and landslide reduction and supported by geographical information system (GIS), remote sensing and database techniques, a DRDSS against debris flow and landslide along highways in mountainous areas has been established on the basis of such principles as pertinence, systematicness, effectiveness, easy to use, open and expandability. The system consists of database, disaster analysis models and decisions on reduction of debris flows and landslides, mainly functioning to zone disaster dangerous degree, analyze debris flow activity, simulate debris flow deposition and diffusion, analyze landslide stability, select optimal highway renovation scheme and plan disaster prevention and control engineering. This system has been applied successfully to the debris flow and landslide treatment works along Palongzangbu Section of Sichuan-Tibet Highway.展开更多
This paper presents a Spatial Decision Support System for local governments of developing countries.It allows municipality government,enterprises,scientific community and civil society to address decision problems usi...This paper presents a Spatial Decision Support System for local governments of developing countries.It allows municipality government,enterprises,scientific community and civil society to address decision problems using GIS.The framework is supported by four modules of information technologies:Environmental Decision Support Database,Data Manipulation,Decision Support,and Mapping.A case study is presented covering the implementation of this framework in one municipality of Cuba.An example of land suitability planning for coconut crops is used to evaluate the system performance and usability.Results show local municipalities are able to use this framework to solve local decision problems using state of the art decision making even with low infrastructure development.展开更多
Critical infrastructures（CI） are designated sectors that if incapacitated or destroyed by natural disasters would have a serious impact on national security and economic and social welfare. Due to the interdependenc...Critical infrastructures（CI） are designated sectors that if incapacitated or destroyed by natural disasters would have a serious impact on national security and economic and social welfare. Due to the interdependency of critical infrastructures failure of one infrastructure during a natural disaster such as earthquake or flood may cause failure of another and so on through a cascade or escalating effect. Quantification of these types of interdependencies between critical infrastructures is essential for effective response and management of resources for rescue, recovery, and restoration during times of crises. This paper proposes a new mathematical framework based on an asymmetric relation matrix constructed in a bottom-up approach for modeling and analyzing interdependencies of critical infrastructures. Asymmetric dependency matrices can be constructed using the asymmetric incidence coefficient based on node-level relationships defined between nodes for measuring the strength of interdependency between node and node, node and network, and networks and networks. These asymmetric matrices are further analyzed for ranking infrastructures in terms of their relative importance and for identifying nodes and infrastructure networks that play a critical role in chain effects among infrastructures involved in geo-disaster events such as flooding. Examples of interdependency analysis for the identification of vulnerabilities among fifteen national defense-related infrastructure sectors by the Australian government and a simulated example using the newly developed GIS-based network simulator Geo PN are used to validate and demonstrate the implementation and effectiveness of interdependency analysis methods in analyzing infrastructure interdependency during a flooding event.展开更多
By applying the system analysis principle and mathematical modeling technique to knowledge expression system for crop cultural management, the fundamental relationships and quantitative algorithms of wheat growth and ...By applying the system analysis principle and mathematical modeling technique to knowledge expression system for crop cultural management, the fundamental relationships and quantitative algorithms of wheat growth and management indices to variety types, ecological environments and production levels were analysed and extracted, and a dynamic knowledge model with temporal and spatial characters for wheat management(WheatKnow)was developed. By adopting the soft component characteristics as non language relevance , re-utilization and portable system maintenance. and by further integrating the wheat growth simulation model(WheatGrow)and intelligent system for wheat management, a comprehensive and digital knowledge model, growth model and component-based decision support system for wheat management(MBDSSWM)was established on the platforms of Visual C++ and Visual Basic. The MBDSSWM realized the effective integration and coupling of the prediction and decision-making functions for digital crop management.展开更多
With the agricultural development and the modernization of decision-making, it is necessary to establish the agricultural sustainable development decision support system supported by GIS. We set Jianli county as an ex...With the agricultural development and the modernization of decision-making, it is necessary to establish the agricultural sustainable development decision support system supported by GIS. We set Jianli county as an example; our aim is to realize decision spatialiazation with the support of information system, remote sensing and artificial intelligence. The system components are described in the aspects of database, knowledge base, model-base and method-base. This system will provide a workable system for local decision-makers and agricultural management sections.展开更多
Hydrological models are often linked with other models in cognate sciences to understand the interactions among climate, earth, water, ecosystem, and human society. This paper presents the development and implementati...Hydrological models are often linked with other models in cognate sciences to understand the interactions among climate, earth, water, ecosystem, and human society. This paper presents the development and implementation of a decision support system（DSS） that links the outputs of hydrological models with real-time decision making on social-economic assessments and land use management. Discharge and glacier geometry changes were simulated with hydrological model, water availability in semiarid environments. Irrigation and ecological water were simulated by a new commercial software MIKE HYDRO. Groundwater was simulated by MODFLOW. All the outputs of theses hydrological models were taken as inputs into the DSS in three types of links： regression equations, stationary data inputs, or dynamic data inputs as the models running parallel in the simulation periods. The DSS integrates the hydrological data, geographic data, social and economic statistical data, and establishes the relationships with equations, conditional statements and fuzzy logics. The programming is realized in C＋＋. The DSS has four remarkable features：（1） editable land use maps to assist decision-making;（2） conjunctive use of surface and groundwater resources;（3） interactions among water, earth, ecosystem, and humans; and（4） links with hydrological models. The overall goal of the DSS is to combine the outputs of scientific models, knowledge of experts, and perspectives of stakeholders, into a computer-based system, which allows sustainability impact assessment within regional planning; and to understand ecosystem services and integrate them into land and water management.展开更多
基金supported by the National Key Research and Development Program (No.2023YFC3502604)the National Natural Science Foundation of China (Nos.U23B2062, 82274352,82174533, 82374302, 82204941)+3 种基金the Noncommunicable Chronic Diseases-National Science and Technology Major Project (No.2023ZD0505700)the Beijing-Tianjin-Hebei Basic Research Cooperation Project (No.22JCZXJC00070)the State Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture (No.SKL2024Z0102)Key R&D project of Ningxia Autonomous Region (No.2022BEG02036).
文摘Traditional Chinese medicine(TCM)represents a paradigmatic approach to personalized medicine,developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years,and now encompasses large-scale electronic medical records(EMR)and experimental molecular data.Artificial intelligence(AI)has demonstrated its utility in medicine through the development of various expert systems(e.g.,MYCIN)since the 1970s.With the emergence of deep learning and large language models(LLMs),AI’s potential in medicine shows considerable promise.Consequently,the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction.This survey provides an insightful overview of TCM AI research,summarizing related research tasks from three perspectives:systems-level biological mechanism elucidation,real-world clinical evidence inference,and personalized clinical decision support.The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice.To critically assess the current state of the field,this work identifies major challenges and opportunities that constrain the development of robust research capabilities—particularly in the mechanistic understanding of TCM syndromes and herbal formulations,novel drug discovery,and the delivery of high-quality,patient-centered clinical care.The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality,large-scale data repositories;the construction of comprehensive and domain-specific knowledge graphs(KGs);deeper insights into the biological mechanisms underpinning clinical efficacy;rigorous causal inference frameworks;and intelligent,personalized decision support systems.
基金supported by the National Research Council of Sri Lanka(Grant No.NRC TO 16-07).
文摘Decision Support Tool(DST)enables farmers to make site-specific crop management decisions;however,comprehensive calibration can be both costly and time-consuming.This study assessed the production and economic benefits of two calibrations of the Nutrient Expert(NE)tool for rice in Sri Lanka’s Alfisols:the basic calibration(Nutrient Expert Sri Lanka 1,NESL1)and the comprehensive calibration(Nutrient Expert Sri Lanka 2,NESL2).NESL1 was developed by adapting the South Indian version of NE to local conditions,while NESL2 was an updated version,using three years of data from 71 farmer fields.
文摘BACKGROUND Cancer care faces challenges due to tumor heterogeneity and rapidly evolving therapies,necessitating artificial intelligence(AI)-driven clinical decision support.While general-purpose models like ChatGPT offer adaptability,domain-specific systems(e.g.,DeepSeek)may better align with clinical guidelines.However,their comparative efficacy in oncology remains underexplored.This study hypothesizes that domain-specific AI will outperform general-purpose models in technical accuracy,while the latter will excel in patient-centered communication.AIMS To compare ChatGPT and DeepSeek in oncology decision support for diagnosis,treatment,and patient communication.METHODS A retrospective analysis was conducted using 1200 anonymized oncology cases(2018–2023)from The Cancer Genome Atlas and institutional databases,covering six cancer types.Each case included histopathology,imaging,genomic profiles,and treatment histories.Both models generated diagnostic interpretations,staging assessments,and therapy recommendations.Performance was evaluated against NCCN/ESMO guidelines and expert oncologist panels using F1-scores,Cohen'sκ,Likert-scale ratings,and readability metrics.Statistical significance was assessed via analysis of variance and post-hoc Tukey tests.RESULTS DeepSeek demonstrated superior performance in diagnostic accuracy(F1-score:89.2%vs ChatGPT's 76.5%,P<0.001)and treatment alignment with guidelines(κ=0.82 vs 0.67,P=0.003).ChatGPT exhibited strengths in patient communi-cation,generating layman-friendly explanations(readability score:8.2/10 vs DeepSeek's 6.5/10,P=0.012).Both models showed limitations in rare cancer subtypes(e.g.,cholangiocarcinoma),with accuracy dropping below 60%.Clinicians rated DeepSeek's outputs as more actionable(4.3/5 vs 3.7/5,P=0.021)but highlighted ChatGPT's utility in palliative care discussions.CONCLUSION Domain-specific AI(DeepSeek)excels in technical precision,while general-purpose models(ChatGPT)enhance patient engagement.A hybrid system integrating both approaches may optimize oncology workflows,contingent on expanded training for rare cancers and real-time guideline updates.
文摘Artificial intelligence(AI)is rapidly transforming radiology and computed tomography(CT)imaging by enabling automated image analysis,improved diagnostic accuracy,and clinical decision-support.We performed a systematic review of peerreviewed studies published between January 1,2010 and March 31,2025 to quantify reported gains in diagnostic performance and workflow efficiency,to evaluate clinical decision-support benefits and risks,and to identify integration priorities.We searched PubMed,IEEE Xplore,Scopus,ScienceDirect,and Google Scholar and screened 128 records;26 studies met the inclusion criteria.Extracted data included study design,AI architecture,sample size,and quantitative performance metrics;study quality was assessed using Newcastle-Ottawa Scales(NOS),Cochrane RoB 2,or AMSTAR 2 as appropriate.Across included studies,AI applications in CT showed consistent improvements in sensitivity,specificity,and time-to-diagnosis in specific tasks(notably lung-nodule detection and intracranial hemorrhage triage),with reported detection-rate increases up to~20%and reduced turnaround times in several real-world implementations.Barriers include dataset bias,limited external validation,interpretability(“black-box”)concerns,workflow integration challenges,and evolving regulatory issues.Economic analyses suggest potentially favorable return on investment(ROI)in high-volume settings but are sensitive to licensing and infrastructure costs.To realize AI's benefits in CT imaging,rigorous multi-center validation,transparent reporting,humancentered workflow design,and post-deployment surveillance are essential.
文摘Background: Clinical decision support tools provide suggestions to support healthcare providers and clinicians, as they attend to patients. Clinicians use these tools to rapidly consult the evidence at the point of care, a practice which has been found to reduce the time patients spend in hospitals, promote the quality of care and improve healthcare outcomes. Such tools include Medscape, VisualDx, Clinical Key, DynaMed, BMJ Best Practice and UpToDate. However, use of such tools has not yet been fully embraced in low-resource settings such as Uganda. Objective: This paper intends to collate data on the use and uptake of one such tool, UpToDate, which was provided at no cost to five medical schools in Uganda. Methods: Free access to UpToDate was granted through the IP addresses of five medical schools in Uganda in collaboration with Better Evidence at The Global Health Delivery Project at Harvard and Brigham and Women’s Hospital and Wolters Kluwer Health. Following the donation, medical librarians in the respective institutions conducted training sessions and created awareness of the tool. Usage data was aggregated, based on logins and content views, presented and analyzed using Excel tables and graphs. Results: The data shows similar trends in increased usage over the period of August 2022 to August 2023 across the five medical schools. The most common topics viewed, mode of access (using either the computer or the mobile app), total usage by institution, ratio of uses to eligible users by institution and ratio of uses to students by institution are shared. Conclusion: The study revealed that the tool was used by various user categories across the institutions with similar steady improved usage over the year. These results can inform the librarians as they encourage their respective institutions to continue using the tool to support uptake of point-of-care tools in clinical practice.
文摘This study presents an AI-driven Spatial Decision Support System (SDSS) aimed at transforming groundwater suitability assessments for domestic and irrigation uses in Visakhapatnam District, Andhra Pradesh, India. By employing advanced remote sensing, GIS, and machine learning techniques, groundwater quality data from 50 monitoring wells, sourced from the Central Ground Water Board (CGWB), was meticulously analysed. Key parameters, including pH, electrical conductivity, total dissolved solids, and major ion concentrations, were evaluated against World Health Organization (WHO) standards to determine domestic suitability. For irrigation, advanced metrics such as Sodium Adsorption Ratio (SAR), Kelly’s Ratio, Residual Sodium Carbonate (RSC), and percentage sodium (% Na) were utilized to assess water quality. The integration of GIS for spatial mapping and AI models for predictive analytics allows for a comprehensive visualization of groundwater quality distribution across the district. Additionally, the irrigation water quality was evaluated using the USA Salinity Laboratory diagram, providing essential insights for effective agricultural water management. This innovative SDSS framework promises to significantly enhance groundwater resource management, fostering sustainable practices for both domestic use and agriculture in the region.
文摘Decision support systems(DSS)based on physically based numerical models are standard tools used by water services and utilities.However,few DSS based on holistic approaches combining distributed hydrological,hydraulic,and hydrogeological models are operationally exploited.This holistic approach was adopted for the development of the AquaVar DSS,used for water resource management in the French Mediterranean Var watershed.The year 2019 marked the initial use of the DSS in its operational environment.Over the next 5 years,multiple hydrological events allowed to test the performance of the DSS.The results show that the tool is capable of simulating peak flows associated with two extreme rainfall events(storms Alex and Aline).For a moderate flood,the real-time functionality was able to simulate forecast discharges 26 h before the flood peak,with a maximum local error of 30%.Finally,simulations for the drought period 2022-2023 highlighted the essential need for DSS to evolve in line with changing climatic conditions,which give rise to unprecedented hydrological processes.The lessons learned from these first 5 years of AquaVar use under operational conditions are synthesized,addressing various topics such as DSS modularity,evolution,data positioning,technology,and governance.
文摘In order to solve existing problems about the method of establishing traditional system structure of decision support system(DSS), O S chart is applied to describe object oriented system structure of general DSS, and a new method of eight specific steps is proposed to establish object oriented system structure of DSS by using the method of O S chart, which is applied successfully to the development of the DSS for the energy system ecology engineering research of the Wangheqiu country. Supplying many scientific effective computing models, decision support ways and a lot of accurate reliable decision data, the DSS plays a critical part in helping engineering researchers to make correct decisions. Because the period for developing the DSS is relatively shorter, the new way improves the efficiency of establishing DSS greatly. It also makes the DSS of system structure more flexible and easy to expand.
基金Supported by National"863"High-tech Project(2006AA10A309)Jilin Technology Gallery Key Project(20060213)~~
文摘In order to solve the problem of the maze precision fertilizer,soil fertility evaluation,soil fertility classify and yield projections,the geographic information system with spatial information processing functions,spatial data mining techniques with spatial information analysis capabilities,expert system technology in the field of artificial intelligence,traditional information management systems and decision support system were effectively integrated in this study,and the statistical analysis method of GIS and data visualization were combined to design and implement the maize precise intelligent space decision-making system.This system had greatly improved the decision-making ability in agricultural production carried out by agricultural management.
基金Supported by the Technology R&D Program of Hebei Province,China~~
文摘[Objective] This study was to provide methods to improve the scientificity and informatization level of agricultural decision-making system based on the study of Decision Support System for ＂Northing of Winter Wheat＂ in Hebei Province （DSS- NWWH）. [Method] The functions, development process, operation guidance as well as input and output modes of DSSNWWH were introduced, and the simulated results of the system were verified by comparing with the actual situations. [Result] The decision support system established in this study could predict whether a wheat variety could live through the winter in a certain area of northern Hebei Province, as well as the growth conditions based on the previous meteorological data or local weather forecast, and provided corresponding cultivation and management measures, making it possible for the user to determine whether the variety could be planted in the region based on the predictions. [Conclusion] The established DSSNWWH in this study can effectively help decision makers make decisions, providing scientific instructions for the northing of winter wheat.
文摘The objectives of this study are to assess land s ui tability and to predict the spatial and temporal changes in land use types (LUTs ) by using GIS-based land use management decision support system. A GIS databas e with data on climate, topography, soil characteristic, irrigation condition, f ertilizer application, and special socioeconomic activities has been developed a nd used for the evaluation of land productivity for different crops by integrati ng with a crop growth model-the erosion productivity impact calculator (EPIC). International food policy simulation model (IFPSIM) is also embedded into GIS fo r the predictions of how crop demands and crop market prices will change under a lternative policy scenarios. An inference engine (IE) including land use choice model is developed to illustrate land use choice behavior based on logit models , which allows to analyze how diversified factors ranging from climate changes, crop price changes to land management changes can affect the distribution of agr icultural land use. A test for integrated simulation is taken in each 0.1° by 0.1° grid cell to predict the change of agricultural land use types at globa l level. Global land use changes are simulated from 1992 to 2050.
文摘Ballistic missile defense system (BMDS) is important for its special role in ensuring national security and maintaining strategic balance. Research on modeling and simulation of the BMDS beforehand is essential as developing a real one requires lots of manpower and resources. BMDS is a typical complex system for its nonlinear, adaptive and uncertainty characteristics. The agent-based modeling method is well suited for the complex system whose overall behaviors are determined by interactions among individual elements. A multi-agent decision support system (DSS), which includes missile agent, radar agent and command center agent, is established based on the studies of structure and function of BMDS. Considering the constraints brought by radar, intercept missile, offensive missile and commander, the objective function of DSS is established. In order to dynamically generate the optimal interception plan, the variable neighborhood negative selection particle swarm optimization (VNNSPSO) algorithm is proposed to support the decision making of DSS. The proposed algorithm is compared with the standard PSO, constriction factor PSO (CFPSO), inertia weight linear decrease PSO (LDPSO), variable neighborhood PSO (VNPSO) algorithm from the aspects of convergence rate, iteration number, average fitness value and standard deviation. The simulation results verify the efficiency of the proposed algorithm. The multi-agent DSS is developed through the Repast simulation platform and the constructed DSS can generate intercept plans automatically and support three-dimensional dynamic display of missile defense process.
基金co-financed by the European Union(European Social Fund-ESF)and Greek national funds through the Operational Program‘‘Education and Lifelong Learning’’of the National Strategic Reference Framework(NSRF)-Research Funding Program:Thales.Investing in knowledge society through the European Social Fund
文摘Forest ecosystems are our priceless natural resource and are a key component of the global carbon budget. Forest fires can be a hazard to the viability and sustainable management of forests with consequences for natural and cultural environments, economies, and the life quality of local and regional populations. Thus, the selection of strategies to manage forest fires, while considering both functional and economic efficiency, is of primary importance. The use of decision support systems(DSSs) by managers of forest fires has rapidly increased. This has strengthened capacity to prevent and suppress forest fires while protecting human lives and property. DSSs are a tool that can benefit incident management and decision making and policy, especially for emergencies such as natural disasters. In this study we reviewed state-of-the-art DSSs that use: database management systems and mathematical/economic algorithms for spatial optimization of firefighting forces; forest fire simulators and satellite technology for immediate detection and prediction of evolution of forest fires; GIS platforms that incorporate several tools to manipulate, process and analyze geographic data and develop strategic and operational plans.
基金Supported by the National Natural Science Foundation of China(No.50909078)the National Basic Research Program of China("973"Program,No.2013CB035900)
文摘It is important and difficult to control the temperature of mass concrete structure during high arch dam construction.A new method with decision support system is presented for temperature control and crack prevention.It is a database system with functions of data storage,information inquiry,data analysis,early warning and resource sharing.Monitoring information during construction can be digitized via this system,and the intelligent analysis and dynamic control of concrete temperature can be conducted.This method has been applied in the construction of the Dagangshan Arch Dam in China and has proven to be very convenient.Based on the decision support of this system and the dynamic adjustment of construction measures,the concrete temperature of this project is well-controlled.
基金Supported by the Knowledge Innovation Program of Chinese Academy of Sciences(KZCX2-306)the National Natural Science Foundation of China(90202007)
文摘Highways in mountainous areas are easy to be damaged by such natural disasters as debris flows and landslides and disaster reduction decision support system (DRDSS) is one of the important means to mitigate these disasters. Guided by the theories and technologies of debris flow and landslide reduction and supported by geographical information system (GIS), remote sensing and database techniques, a DRDSS against debris flow and landslide along highways in mountainous areas has been established on the basis of such principles as pertinence, systematicness, effectiveness, easy to use, open and expandability. The system consists of database, disaster analysis models and decisions on reduction of debris flows and landslides, mainly functioning to zone disaster dangerous degree, analyze debris flow activity, simulate debris flow deposition and diffusion, analyze landslide stability, select optimal highway renovation scheme and plan disaster prevention and control engineering. This system has been applied successfully to the debris flow and landslide treatment works along Palongzangbu Section of Sichuan-Tibet Highway.
基金This paper has been supported by the project 2009DFA13000 funded by the Ministry of Science and Technology of the People’s Republic of China.The authors want to thank the researchers from Instituto de Investigaciones en Fruticultura Tropical,Republic of Cuba,in special Dr Jorge Cuetothe staff of Nipe-Sagua-Baracoa mountain office,and the government of Baracoa for their kind support and advice.
文摘This paper presents a Spatial Decision Support System for local governments of developing countries.It allows municipality government,enterprises,scientific community and civil society to address decision problems using GIS.The framework is supported by four modules of information technologies:Environmental Decision Support Database,Data Manipulation,Decision Support,and Mapping.A case study is presented covering the implementation of this framework in one municipality of Cuba.An example of land suitability planning for coconut crops is used to evaluate the system performance and usability.Results show local municipalities are able to use this framework to solve local decision problems using state of the art decision making even with low infrastructure development.
基金finically supported by a project “Modeling Infrastructure Interdependency for Emergency Management Using a Network-Centric Spatial Decision Support System Approach” awarded jointly by the Natural Science and Engineering Research Council of Canada (NSERC)the Public Safety and Emergency Preparedness Canada (PSEPC) (No.JIIRP 312733-04)
文摘Critical infrastructures（CI） are designated sectors that if incapacitated or destroyed by natural disasters would have a serious impact on national security and economic and social welfare. Due to the interdependency of critical infrastructures failure of one infrastructure during a natural disaster such as earthquake or flood may cause failure of another and so on through a cascade or escalating effect. Quantification of these types of interdependencies between critical infrastructures is essential for effective response and management of resources for rescue, recovery, and restoration during times of crises. This paper proposes a new mathematical framework based on an asymmetric relation matrix constructed in a bottom-up approach for modeling and analyzing interdependencies of critical infrastructures. Asymmetric dependency matrices can be constructed using the asymmetric incidence coefficient based on node-level relationships defined between nodes for measuring the strength of interdependency between node and node, node and network, and networks and networks. These asymmetric matrices are further analyzed for ranking infrastructures in terms of their relative importance and for identifying nodes and infrastructure networks that play a critical role in chain effects among infrastructures involved in geo-disaster events such as flooding. Examples of interdependency analysis for the identification of vulnerabilities among fifteen national defense-related infrastructure sectors by the Australian government and a simulated example using the newly developed GIS-based network simulator Geo PN are used to validate and demonstrate the implementation and effectiveness of interdependency analysis methods in analyzing infrastructure interdependency during a flooding event.
基金supported by the National Natural Science Foundation of China(30030090)the National 863 Program,China(2001AA115420,2001AA245041).
文摘By applying the system analysis principle and mathematical modeling technique to knowledge expression system for crop cultural management, the fundamental relationships and quantitative algorithms of wheat growth and management indices to variety types, ecological environments and production levels were analysed and extracted, and a dynamic knowledge model with temporal and spatial characters for wheat management(WheatKnow)was developed. By adopting the soft component characteristics as non language relevance , re-utilization and portable system maintenance. and by further integrating the wheat growth simulation model(WheatGrow)and intelligent system for wheat management, a comprehensive and digital knowledge model, growth model and component-based decision support system for wheat management(MBDSSWM)was established on the platforms of Visual C++ and Visual Basic. The MBDSSWM realized the effective integration and coupling of the prediction and decision-making functions for digital crop management.
基金Supported by the National Natural Science Foundation of China (4 98710 71)
文摘With the agricultural development and the modernization of decision-making, it is necessary to establish the agricultural sustainable development decision support system supported by GIS. We set Jianli county as an example; our aim is to realize decision spatialiazation with the support of information system, remote sensing and artificial intelligence. The system components are described in the aspects of database, knowledge base, model-base and method-base. This system will provide a workable system for local decision-makers and agricultural management sections.
基金supported by German-Sino bilateral collaboration research project SuMaRiO funded by the German Federal Ministry of Education and Researchthe support of NSFC-UNEP Project (41361140361): Ecological Responses to Climatic Change and Land-cover Change in Arid and Semiarid Central Asia during the Past 500 Years
文摘Hydrological models are often linked with other models in cognate sciences to understand the interactions among climate, earth, water, ecosystem, and human society. This paper presents the development and implementation of a decision support system（DSS） that links the outputs of hydrological models with real-time decision making on social-economic assessments and land use management. Discharge and glacier geometry changes were simulated with hydrological model, water availability in semiarid environments. Irrigation and ecological water were simulated by a new commercial software MIKE HYDRO. Groundwater was simulated by MODFLOW. All the outputs of theses hydrological models were taken as inputs into the DSS in three types of links： regression equations, stationary data inputs, or dynamic data inputs as the models running parallel in the simulation periods. The DSS integrates the hydrological data, geographic data, social and economic statistical data, and establishes the relationships with equations, conditional statements and fuzzy logics. The programming is realized in C＋＋. The DSS has four remarkable features：（1） editable land use maps to assist decision-making;（2） conjunctive use of surface and groundwater resources;（3） interactions among water, earth, ecosystem, and humans; and（4） links with hydrological models. The overall goal of the DSS is to combine the outputs of scientific models, knowledge of experts, and perspectives of stakeholders, into a computer-based system, which allows sustainability impact assessment within regional planning; and to understand ecosystem services and integrate them into land and water management.
