Polymer informatics faces challenges owing to data scarcity arising from complex chemistries,experimental limitations,and process-ing-dependent properties.This review presents the recent advances in data-efficient mac...Polymer informatics faces challenges owing to data scarcity arising from complex chemistries,experimental limitations,and process-ing-dependent properties.This review presents the recent advances in data-efficient machine learning for polymers.First,data preparation tech-niques such as data augmentation and rational representation help expand the dataset size and develop useful features for learning.Second,modeling approaches,including classical algorithms and physics-informed methods,enhance the model robustness and reliability under limited data conditions.Third,learning strategies,such as transferlearning and active learning,aim to improve generalization and guide efficient data ac-quisition.This review concludes by outlining future opportunities in machine learning for small-data scenarios in polymers.This review is expect-ed to serve as a useful tool for newcomers and offer deeper insights for experienced researchers in the field.展开更多
This study aimed to evaluate the correlation between nursing informatics(NI)competency and information literacy skills for evidencebased practice(EBP)among intensive care nurses.This cross-sectional study was conducte...This study aimed to evaluate the correlation between nursing informatics(NI)competency and information literacy skills for evidencebased practice(EBP)among intensive care nurses.This cross-sectional study was conducted on 184 nurses working in intensive care units(ICUs).The study data were collected through demographic information,Nursing Informatics Competency Assessment Tool(NICAT),and information literacy skills for EBP questionnaires.The intensive care nurses received competent and low-moderate levels for the total scores of NI competency and information literacy skills,respectively.They received a moderate score for the use of different information resources but a low score for information searching skills,different search features,and knowledge about search operators,and only 31.5%of the nurses selected the most appropriate statement.NI competency and related subscales had a significant direct bidirectional correlation with information literacy skills for EBP and its subscales(P<0.05).Nurses require a high level of NI competency and information literacy for EBP to obtain up-to-date information and provide better care and decision-making.Health planners and policymakers should develop interventions to enhance NI competency and information literacy skills among nurses and motivate them to use EBP in clinical settings.展开更多
Due to the recent developments in communications technology,cognitive computations have been used in smart healthcare techniques that can combine massive medical data,artificial intelligence,federated learning,bio-ins...Due to the recent developments in communications technology,cognitive computations have been used in smart healthcare techniques that can combine massive medical data,artificial intelligence,federated learning,bio-inspired computation,and the Internet of Medical Things.It has helped in knowledge sharing and scaling ability between patients,doctors,and clinics for effective treatment of patients.Speech-based respiratory disease detection and monitoring are crucial in this direction and have shown several promising results.Since the subject’s speech can be remotely recorded and submitted for further examination,it offers a quick,economical,dependable,and noninvasive prospective alternative detection approach.However,the two main requirements of this are higher accuracy and lower computational complexity and,in many cases,these two requirements do not correlate with each other.This problem has been taken up in this paper to develop a low computational complexity-based neural network with higher accuracy.A cascaded perceptual functional link artificial neural network(PFLANN)is used to capture the nonlinearity in the data for better classification performance with low computational complexity.The proposed model is being tested for multiple respiratory diseases,and the analysis of various performance matrices demonstrates the superior performance of the proposed model both in terms of accuracy and complexity.展开更多
Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic outbreaks.This review discusses the current state of SM...Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic outbreaks.This review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their performance.Since,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by SM.This paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM,along with the ML and DL techniques that have been configured for the detection of epidemic outbreaks.DL has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation results.In recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in SM analysis.This paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM analysis.Finally,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.展开更多
Since the establishment of the Collaboratory for the Study of Earthquake Predictability,China(CSEP-CN)center,no comprehensive study has been conducted on the parameter models of the Pattern Informatics(PI)method withi...Since the establishment of the Collaboratory for the Study of Earthquake Predictability,China(CSEP-CN)center,no comprehensive study has been conducted on the parameter models of the Pattern Informatics(PI)method within the China Seismic Experimental Site(CSES)region.Additionally,the boundary issues of the study area have been a subject of ongoing debate.Tian et al.(2024)indicates that variations in seismic activity within the region impact the predictive efficacy of the PI method.展开更多
In 2022,four earthquakes with M_(S)≥6.0 including the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes occurred in the North-South Seismic Zone(NSSZ),which demonstrated high and strong seismicity.Pattern Informatics(...In 2022,four earthquakes with M_(S)≥6.0 including the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes occurred in the North-South Seismic Zone(NSSZ),which demonstrated high and strong seismicity.Pattern Informatics(PI)method,as an effective long and medium term earthquake forecasting method,has been applied to the strong earthquake forecasting in Chinese mainland and results have shown the positive performance.The earthquake catalog with magnitude above M_(S)3.0 since 1970 provided by China Earthquake Networks Center was employed in this study and the Receiver Operating Characteristic(ROC)method was applied to test the forecasting efficiency of the PI method in each selected region related to the North-South Seismic Zone systematically.Based on this,we selected the area with the best ROC testing result and analyzed the evolution process of the PI hotspot map reflecting the small seismic activity pattern prior to the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes.A“forward”forecast for the area was carried out to assess seismic risk.The study shows the following.1)PI forecasting has higher forecasting efficiency in the selected study region where the difference of seismicity in any place of the region is smaller.2)In areas with smaller differences of seismicity,the activity pattern of small earthquakes prior to the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes can be obtained by analyzing the spatio-temporal evolution process of the PI hotspot map.3)The hotspot evolution in and around the southern Tazang fault in the study area is similar to that prior to the strong earthquakes,which suggests the possible seismic hazard in the future.This study could provide some ideas to the seismic hazard assessment in other regions with high seismicity,such as Japan,Californi,Turkey,and Indonesia.展开更多
Water quality system informatics(WQSI)is an emerging field that employs cybernetics to collect and digitize data associated with water quality.It involves monitoring the physical,chemical,and biological processes that...Water quality system informatics(WQSI)is an emerging field that employs cybernetics to collect and digitize data associated with water quality.It involves monitoring the physical,chemical,and biological processes that affect water quality and the ecological impacts and interconnections within water quality systems.WQSI integrates theories and methods from water quality engineering,information engineering,and system control theory,enabling the intelligent management and control of water quality.This integration revolutionizes the understanding and management of water quality systems with greater precision and higher resolution.WQSI is a new stage of development in environmental engineering that is driven by the digital age.This work explores the fundamental concepts,research topics,and methods of WQSI and its features and potential to promote disciplinary development.The innovation and development of WQSI are crucial for driving the digital and intelligent transformation of national industry patterns in China,positioning China at the forefront of environmental engineering and ecological environment research on a global scale.展开更多
Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),...Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。展开更多
Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),...Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。展开更多
Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),...Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。展开更多
Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),...Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。展开更多
Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),...Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。展开更多
Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),...Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。展开更多
Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),...Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。展开更多
Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),...Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。展开更多
Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),...Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。展开更多
Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),...Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。展开更多
Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),...Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士。展开更多
Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),...Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。展开更多
Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),...Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。展开更多
基金supported by the National Natural Science Foundation of China(No.22473006)the Central Government Guiding Local Science and Technology Development Fund(No.2025ZY01029).
文摘Polymer informatics faces challenges owing to data scarcity arising from complex chemistries,experimental limitations,and process-ing-dependent properties.This review presents the recent advances in data-efficient machine learning for polymers.First,data preparation tech-niques such as data augmentation and rational representation help expand the dataset size and develop useful features for learning.Second,modeling approaches,including classical algorithms and physics-informed methods,enhance the model robustness and reliability under limited data conditions.Third,learning strategies,such as transferlearning and active learning,aim to improve generalization and guide efficient data ac-quisition.This review concludes by outlining future opportunities in machine learning for small-data scenarios in polymers.This review is expect-ed to serve as a useful tool for newcomers and offer deeper insights for experienced researchers in the field.
文摘This study aimed to evaluate the correlation between nursing informatics(NI)competency and information literacy skills for evidencebased practice(EBP)among intensive care nurses.This cross-sectional study was conducted on 184 nurses working in intensive care units(ICUs).The study data were collected through demographic information,Nursing Informatics Competency Assessment Tool(NICAT),and information literacy skills for EBP questionnaires.The intensive care nurses received competent and low-moderate levels for the total scores of NI competency and information literacy skills,respectively.They received a moderate score for the use of different information resources but a low score for information searching skills,different search features,and knowledge about search operators,and only 31.5%of the nurses selected the most appropriate statement.NI competency and related subscales had a significant direct bidirectional correlation with information literacy skills for EBP and its subscales(P<0.05).Nurses require a high level of NI competency and information literacy for EBP to obtain up-to-date information and provide better care and decision-making.Health planners and policymakers should develop interventions to enhance NI competency and information literacy skills among nurses and motivate them to use EBP in clinical settings.
文摘Due to the recent developments in communications technology,cognitive computations have been used in smart healthcare techniques that can combine massive medical data,artificial intelligence,federated learning,bio-inspired computation,and the Internet of Medical Things.It has helped in knowledge sharing and scaling ability between patients,doctors,and clinics for effective treatment of patients.Speech-based respiratory disease detection and monitoring are crucial in this direction and have shown several promising results.Since the subject’s speech can be remotely recorded and submitted for further examination,it offers a quick,economical,dependable,and noninvasive prospective alternative detection approach.However,the two main requirements of this are higher accuracy and lower computational complexity and,in many cases,these two requirements do not correlate with each other.This problem has been taken up in this paper to develop a low computational complexity-based neural network with higher accuracy.A cascaded perceptual functional link artificial neural network(PFLANN)is used to capture the nonlinearity in the data for better classification performance with low computational complexity.The proposed model is being tested for multiple respiratory diseases,and the analysis of various performance matrices demonstrates the superior performance of the proposed model both in terms of accuracy and complexity.
基金authors are thankful to the Deanship of Scientific Research at Najran University for funding this work,under the Research Groups Funding Program Grant Code(NU/RG/SERC/12/27).
文摘Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic outbreaks.This review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their performance.Since,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by SM.This paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM,along with the ML and DL techniques that have been configured for the detection of epidemic outbreaks.DL has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation results.In recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in SM analysis.This paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM analysis.Finally,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.
基金supported by the Joint Funds of the National Natural Science Foundation of China(Grant No.U2039207).
文摘Since the establishment of the Collaboratory for the Study of Earthquake Predictability,China(CSEP-CN)center,no comprehensive study has been conducted on the parameter models of the Pattern Informatics(PI)method within the China Seismic Experimental Site(CSES)region.Additionally,the boundary issues of the study area have been a subject of ongoing debate.Tian et al.(2024)indicates that variations in seismic activity within the region impact the predictive efficacy of the PI method.
基金the National Natural Science Foundation of China Study on the Theory and Methods of Deterministic-Probabilistic(No.U2039207)the National Key Research and Development Program of China‘CSEP China in the Context of China Seismic Experimental Site’(No.2018YFE0109700).
文摘In 2022,four earthquakes with M_(S)≥6.0 including the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes occurred in the North-South Seismic Zone(NSSZ),which demonstrated high and strong seismicity.Pattern Informatics(PI)method,as an effective long and medium term earthquake forecasting method,has been applied to the strong earthquake forecasting in Chinese mainland and results have shown the positive performance.The earthquake catalog with magnitude above M_(S)3.0 since 1970 provided by China Earthquake Networks Center was employed in this study and the Receiver Operating Characteristic(ROC)method was applied to test the forecasting efficiency of the PI method in each selected region related to the North-South Seismic Zone systematically.Based on this,we selected the area with the best ROC testing result and analyzed the evolution process of the PI hotspot map reflecting the small seismic activity pattern prior to the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes.A“forward”forecast for the area was carried out to assess seismic risk.The study shows the following.1)PI forecasting has higher forecasting efficiency in the selected study region where the difference of seismicity in any place of the region is smaller.2)In areas with smaller differences of seismicity,the activity pattern of small earthquakes prior to the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes can be obtained by analyzing the spatio-temporal evolution process of the PI hotspot map.3)The hotspot evolution in and around the southern Tazang fault in the study area is similar to that prior to the strong earthquakes,which suggests the possible seismic hazard in the future.This study could provide some ideas to the seismic hazard assessment in other regions with high seismicity,such as Japan,Californi,Turkey,and Indonesia.
基金the support provided by the National Natural Science Foundation of China(52327813,52131003,and 52370058)the Outstanding Scientist of Chongqing Talent Plan(CQYC20210101288 and CQYC202101006)。
文摘Water quality system informatics(WQSI)is an emerging field that employs cybernetics to collect and digitize data associated with water quality.It involves monitoring the physical,chemical,and biological processes that affect water quality and the ecological impacts and interconnections within water quality systems.WQSI integrates theories and methods from water quality engineering,information engineering,and system control theory,enabling the intelligent management and control of water quality.This integration revolutionizes the understanding and management of water quality systems with greater precision and higher resolution.WQSI is a new stage of development in environmental engineering that is driven by the digital age.This work explores the fundamental concepts,research topics,and methods of WQSI and its features and potential to promote disciplinary development.The innovation and development of WQSI are crucial for driving the digital and intelligent transformation of national industry patterns in China,positioning China at the forefront of environmental engineering and ecological environment research on a global scale.
文摘Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。
文摘Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。
文摘Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。
文摘Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。
文摘Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。
文摘Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。
文摘Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。
文摘Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。
文摘Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。
文摘Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。
文摘Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。
文摘Informatics and Health(《信息学与健康》)是由中国医学科学院北京协和医学院主办,中国医学科学院医学信息研究所与科爱公司合作编辑出版,旨在反映医学卫生健康领域与信息科学技术相关的前沿学术研究进展的英文期刊(ISSN:2949-9534),本刊由中国工程院院士、中国医学科学院北京协和医学院院校长王辰教授担任主编,中国医学科学院医学信息研究所所长刘辉研究员担任执行主编。
