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Model of developing key performance indicator to increase the quality of education during the Covid-19 pandemic

Journal of Physics: Conference Series 2021年第1期1832卷

作者： E Selviyanti W Sardjono M Mukhlis M Tohir M Maswar A Fariz Health Department Politeknik Negeri Jember Jember Jawa Timur Indonesia 68124 Information Systems Management Department BINUS Graduate Program – Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 Faculty of Teacher Training and Education Islamic State Institute of Jember Jawa Timur INDONESIA Universitas Ibrahimy Situbondo Indonesia Computer Network Engineering SMK 3 Perguruan 'Cikini' Jakarta Indonesia 12640

Indonesia is one of the countries whose people are most affected by the 2019 corona virus (COVID-19). When the corona virus spreads faster, the Indonesian government imposed large-scale social restrictions in big cities to villages in Indonesia. With the changing situation in carrying out work activities during this pandemic, it will certainly affect the quality of organization in companies and the quality of education in schools and colleges. In order to identify all processes in teaching and learning activities that are running well or not, schools need to monitor and measure employee performance. Key performance indicators (KPIs) are generally used as benchmarks to determine how well a company's performance can be represented by employee performance. In this study, the key performance indicator preparation process was carried out through the stages of designing a questionnaire, distributing questionnaires to employees in educational institutions, conducting factor analysis and then developing a KPI model. The output is in the form of a KPI model that can be used as a reference in the formation of KPIs in educational institutions, namely Y = 5,360 + 1,380 X1-1, 068 X3.

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The Affecting Factors of Blockchain Technology Adoption of Payments systems in Indonesia Banking Industry 3

The Affecting Factors of Blockchain Technology Adoption of P...

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3rd International Conference on information Management and Technology, ICIMTech 2018

作者： Taufiq, Rohmat Meyliana Hidayanto, Achmad Nizar Prabowo, Harjanto Computer Science Department BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Informatic Engineering Engineering Faculty University Muhammadiyah of Tangerang Tangerang15117 Indonesia Information Systems Department Bina Nusantara University School of Information Systems Jakarta11480 Indonesia Faculty of Computer Science University of Indonesia Depok16424 Indonesia Management Department Bina Nusantara University BINUS Business School Undergraduate Program Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

The purpose of this study is to find the influence factors of blockchain technology adoption of payments system in Indonesia banking industry. Moreover, the researchers proposed new model of payment system by using blockchain technology in Indonesia banking industry. All this time, the researchers of blockchain in payment systems were done in major countries such as UK, USA, Australia, Scotland, Germany, Japan, France, Italy, and China. Systematic Literature Review (SLR) used as a method in this study and there were five databases that taken as references, such as IEEE, Science direct, AIS electronic, ACM and Google Scholar. The researchers were found 26 references Studies Included in Quantitative Synthesis and 9 variables (Easy to use, Usefulness, Transaction fees, Risk perception, Behaviour intention of use, Attitude toward, Cognitive style, Subjective Norm, Effectiveness). Based on the result of data analysis and discussion, there were two conclusions in this study, the first, the researchers found nine factors that expected tobe used as a reference if Indonesia banking industry wants to adopt blockchain technology for payment system;and second, the researchers had to propose payment system model by using blockchain technology in Indonesia banking industry. © 2018 IEEE.

关键词： Blockchain

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Designing an Institutional Research Management System Framework for Higher Education 3

Designing an Institutional Research Management System Framew...

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3rd International Conference on information Management and Technology, ICIMTech 2018

作者： Noerlina Elda Hiererra, Siti Saleh Abbas, Bahtiar Andro Makalew, Brilly Maya Kristin, Desi Nugraha Mursitama, Tirta David Information Systems Department Bina Nusantara University School of Information Systems Jakarta11480 Indonesia Industrial Engineering Department Faculty of Engineering Bina Nusantara University Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Mobile Application Technology Program Jakarta11480 Indonesia Computer Science Department Bina Nusantara University School of Computer Science Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

Although research activity plays a big role in institutional ranking and provides a great benefit for university lecturer, the process of managing all research activity is tedious and exhausting. In most university, management must be able to collect all hundreds of proposals and reports;not to mention they must be able to accommodate the process of reviewing every single proposal. They also need to monitor all research output in final report and make sure that all of the outputs are correctly achieved from proposed target. In addition to the problems stated, previous activities are done manually, leaving a lot of opportunity to improve and automate the process. All of the addressable opportunity for improvement are explained and explored, thus a model of the web application is created. This paper presents the design of web application used to solve persistent problem in research management, specifically in Binus University. The design methodology is divided into two phases: requirement engineering phase, and system design. Upon finishing the requirement engineering phase, system model is depicted using Unified Modeling Language, specifically: Activity Diagram, Use Case Diagram, and Conceptual Class Diagram. © 2018 IEEE.

关键词： Unified Modeling Language

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Technology Roadmap for Flexible Sensors

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ACS NANO 2023年第6期17卷 5211-5295页

作者： Luo, Yifei Abidian, Mohammad Reza Ahn, Jong-Hyun Akinwande, Deji Andrews, Anne M. Antonietti, Markus Bao, Zhenan Berggren, Magnus Berkey, Christopher A. Bettinger, Christopher John Chen, Jun Chen, Peng Cheng, Wenlong Cheng, Xu Choi, Seon-Jin Chortos, Alex Dagdeviren, Canan Dauskardt, Reinhold H. Di, Chong-an Dickey, Michael D. Duan, Xiangfeng Facchetti, Antonio Fan, Zhiyong Fang, Yin Feng, Jianyou Feng, Xue Gao, Huajian Gao, Wei Gong, Xiwen Guo, Chuan Fei Guo, Xiaojun Hartel, Martin C. He, Zihan Ho, John S. Hu, Youfan Huang, Qiyao Huang, Yu Huo, Fengwei Hussain, Muhammad M. Javey, Ali Jeong, Unyong Jiang, Chen Jiang, Xingyu Kang, Jiheong Karnaushenko, Daniil Khademhosseini, Ali Kim, Dae-Hyeong Kim, Il-Doo Kireev, Dmitry Kong, Lingxuan Lee, Chengkuo Lee, Nae-Eung Lee, Pooi See Lee, Tae-Woo Li, Fengyu Li, Jinxing Liang, Cuiyuan Lim, Chwee Teck Lin, Yuanjing Lipomi, Darren J. Liu, Jia Liu, Kai Liu, Nan Liu, Ren Liu, Yuxin Liu, Yuxuan Liu, Zhiyuan Liu, Zhuangjian Loh, Xian Jun Lu, Nanshu Lv, Zhisheng Magdassi, Shlomo Malliaras, George G. Matsuhisa, Naoji Nathan, Arokia Niu, Simiao Pan, Jieming Pang, Changhyun Pei, Qibing Peng, Huisheng Qi, Dianpeng Ren, Huaying Rogers, John A. Rowe, Aaron Schmidt, Oliver G. Sekitani, Tsuyoshi Seo, Dae-Gyo Shen, Guozhen Sheng, Xing Shi, Qiongfeng Someya, Takao Song, Yanlin Stavrinidou, Eleni Su, Meng Sun, Xuemei Takei, Kuniharu Tao, Xiao-Ming Tee, Benjamin C. K. Thean, Aaron Voon-Yew Trung, Tran Quang Wan, Changjin Wang, Huiliang Wang, Joseph Wang, Ming Wang, Sihong Wang, Ting Wang, Zhong Lin Weiss, Paul S. Wen, Hanqi Xu, Sheng Xu, Tailin Yan, Hongping Yan, Xuzhou Yang, Hui Yang, Le Yang, Shuaijian Yin, Lan Yu, Cunjiang Yu, Guihua Yu, Jing Yu, Shu-Hong Yu, Xinge Zamburg, Evgeny Zhang, Haixia Zhang, Xiangyu Zhang, Xiaosheng Zhang, Xueji Zhang, Yihui Zhang, Yu Zhao, Siyuan Zhao, Xuanhe Zheng, Yuanjin Zheng, Yu-Qing Zheng, Zijian Zhou, Tao Zhu, Bowen Zhu, Ming Zhu, Rong Zhu, Yangzhi Zhu, Yong Zou, Guijin Chen, Xiaodong 08-03 Innovis Singapore 138634 Republic of Singapore Innovative Centre for Flexible Devices (iFLEX) School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Department of Biomedical Engineering University of Houston Houston Texas 77024 United States School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 United States Microelectronics Research Center The University of Texas at Austin Austin Texas 78758 United States Department of Chemistry and Biochemistry California NanoSystems Institute and Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior and Hatos Center for Neuropharmacology University of California Los Angeles Los Angeles California 90095 United States Colloid Chemistry Department Max Planck Institute of Colloids and Interfaces 14476 Potsdam Germany Department of Chemical Engineering Stanford University Stanford California 94305 United States Laboratory of Organic Electronics Department of Science and Technology Campus Norrköping Linköping University 83 Linköping Sweden Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC) SE-100 44 Stockholm Sweden Department of Materials Science and Engineering Stanford University Stanford California 94301 United States Department of Biomedical Engineering and Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Department of Bioengineering University of California Los Angeles Los Angeles California 90095 United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637457 Singapore Nanobionics Group Department of Chemical and Biological Engineering Monash University Clayton Australia 3800 Monash

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative

关键词： soft materials mechanics engineering flexible electronics conformable sensors bioelectronics human-machine interfaces body area sensor networks technology translation sustainable electronics

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Cluster Analysis Application at the Five Largest Airports in Indonesia to Carry Out a Tax-Free Policy

Cluster Analysis Application at the Five Largest Airports in...

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2018 International Conference on ICT for Smart Society, ICISS 2018

作者： Condrobimo, A. Raharto Nindito, Hendro Dian Sano, Albert V. Kosala, Raymond Ranti, Benny Harso Supangkat, Suhono Computer Science Department BINUS Graduated Program-Computer Science Bina Nusantara University Jakarta11480 Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Computer Science Institut Teknologi Kreatif Bina Nusantara Malang65126 Indonesia Faculty of Computer Science Universitas Indonesia Depok16424 Indonesia Sekolah Teknik Elektro Dan Informatika Institut Teknologi Bandung Bandung Indonesia

ISBN: (纸本)9781538665893

The objective of this study is to apply cluster analysis on Indonesia's international tourism data set. Algorithm used in this cluster analysis is k-means and the number of cluster (k) is four and the similarity measurement between members of clusters is based on Euclidean distance. The source of data set was taken from Ministry of Tourism portal of Republic of Indonesia per November 2017. The results of this cluster analysis is presented in a table consisting of four clusters and each cluster consists of its members. Cluster analysis in this study can be used more quickly and efficiently to identify countries which will be the promotional and campaign targets on tax-free incentives for foreign tourists assuming a constraint that promotional and campaign budgets are always limited so that the related policy makers need to set a priority on targeted countries. © 2018 IEEE.

关键词： Data mining

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Left ventricular hypertrophy detection using electrocardiographic signal

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Scientific reports 2023年第1期13卷 2556页

作者： Cheng-Wei Liu Fu-Hsing Wu Yu-Lun Hu Ren-Hao Pan Chuen-Horng Lin Yung-Fu Chen Guo-Shiang Tseng Yung-Kuan Chan Ching-Lin Wang Division of Cardiology Department of Internal Medicine Tri-Service General Hospital Songshan Branch National Defense Medical Center Taipei Taiwan. Bachelor Degree Program of Artificial Intelligence National Taichung University of Science and Technology Taichung Taiwan. Department of Management Information Systems National Chung-Hsing University Taichung Taiwan. La Vida Tec. Co. Ltd. Taichung Taiwan. Preventive Medicine Center National Yang Ming Chiao Tung University Taipei Taiwan. Department of Information Management Tunghai University Taichung Taiwan. Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taichung Taiwan. Department of Dental Technology and Materials Science Central Taiwan University of Science and Technology Taichung Taiwan. Division of Cardiology Department of Internal Medicine Taoyuan Armed Force General Hospital Hsinchu Branch Hsinchu Taiwan. Department of Management Information Systems National Chung-Hsing University Taichung Taiwan. ykchan@nchu.edu.tw. Department of Information Management National Chin-Yi University of Technology Taichung Taiwan. clwang@ncut.edu.tw.

Left ventricular hypertrophy (LVH) indicates subclinical organ damage, associating with the incidence of cardiovascular diseases. From the medical perspective, electrocardiogram (ECG) is a low-cost, non-invasive, and easily reproducible tool that is often used as a preliminary diagnosis for the detection of heart disease. Nowadays, there are many criteria for assessing LVH by ECG. These criteria usually include that voltage combination of RS peaks in multi-lead ECG must be greater than one or more thresholds for diagnosis. We developed a system for detecting LVH using ECG signals by two steps: firstly, the R-peak and S-valley amplitudes of the 12-lead ECG were extracted to automatically obtain a total of 24 features and ECG beats of each case (LVH or non-LVH) were segmented; secondly, a back propagation neural network (BPN) was trained using a dataset with these features. Echocardiography (ECHO) was used as the gold standard for diagnosing LVH. The number of LVH cases (of a Taiwanese population) identified was 173. As each ECG sequence generally included 8 to 13 cycles (heartbeats) due to differences in heart rate, etc., we identified 1466 ECG cycles of LVH patients after beat segmentation. Results showed that our BPN model for detecting LVH reached the testing accuracy, precision, sensitivity, and specificity of 0.961, 0.958, 0.966 and 0.956, respectively. Detection performances of our BPN model, on the whole, outperform 7 methods using ECG criteria and many ECG-based artificial intelligence (AI) models reported previously for detecting LVH.

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Implementation on Indonesian property real estate industry based on service oriented architecture

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IOP Conference Series: Materials Science and Engineering 2020年第1期725卷

作者： Ahmad Nurul Fajar Nunung Nurul Qomariyah Albert Baihaqi Siregar Information Systems Management Department BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department Faculty of Computing and Media Bina Nusantara University Jakarta Indonesia 11480 Department of Information Technology Universitas Sumatera Utara Medan Indonesia

This study focuses on the implementation of business property in real estate market. This is due to inability of the current technology to support the property products. Some people feel uncomfortable to buy houses from the online market. Buyers need to be very careful to deal with the sellers as the houses price is considered quite expensive. On the other hand, improving real estate market is still a challenge. This business still needs a physical representation, although it can be sold from the online market. In this paper, we propose the Service Oriented Architecture (SOA) system of virtual reality and drone. We use drone to help scanning the property units and then make 3D models with visual mapping so it can be run in a virtual reality environment, video 360. In real estate, business process can be developed in various ways. Our proposed SOA in this study can be used to integrate all of them.

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Health Assistant Wearable-Based Data Science System Model: A Pilot Study 3

Health Assistant Wearable-Based Data Science System Model: A...

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3rd International Conference on information Management and Technology, ICIMTech 2018

作者： Budiarto, Arif Febriana, Trisna Suparyanto, Teddy Caraka, Rezzy Eko Pardamean, Bens Computer Science Department Bina Nusantara University School of Computer Science Jakarta11480 Indonesia Information Systems Department Bina Nusantara University School of Information Systems Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Indonesia Faculty of Science National University of Malaysia School of Mathematical Science Bangi43000 Malaysia Computer Science Department Bina Nusantara University BINUS Graduate Program-Master of Computer Science Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

The rapid development of information and Communication Technology (ICT) has an impact on the innovation of new technology that gives benefits for health. One of its latest development is wearable device technology. Nowadays, the growth of this technology market is very positive. But unfortunately the growth of this technology is not followed by the availability of supporting applications that provide maximum benefits for users by utilizing personal health and activity data. This paper is intended to provide a report of our initial research in developing a health assistant solution that utilizes wearable device generated data. The whole research process is executed using Design Thinking approach that put the users as the main consideration. This initial research is started by designing a field research that can potentially gathered users' data generated from wearable device. A series of statistical and machine learning techniques are presented to analyze time series data to create a model. Finally, to implement the model, a mobile application prototype is also proposed. The outcomes from this initial research will be used to develop a fully working solution. © 2018 IEEE.

关键词： Learning systems

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The Trigger Factors and Constraints on e-Supply Chain Processes: A Systematic Literature Review 3

The Trigger Factors and Constraints on e-Supply Chain Proces...

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3rd International Conference on information Management and Technology, ICIMTech 2018

作者： Maniah Meyliana Hidayanto, Achmad Nizar Prabowo, Harjanto Gaol, Ford Lumban Computer Science Department Bina Nusantara University Major of Informatics Management Jakarta Bandung11480 Indonesia Information Systems Department Bina Nusantara University School of Information Systems Jakarta Indonesia11480 Indonesia Faculty of Computer Science University of Indonesia Depok16424 Indonesia Management Department Bina Nusantara University BINUS Business School Undergraduate Program Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

The development of information technology will certainly have a major influence on all aspects of life, not least for companies engaged in the supply chain. The role of information technology and electronic networks in running a supply chain is called the Electronic Supply Chain (e-Supply Chain). The main point of this research is to conduct a literature review to find the trigger factors and constraints in the e-supply chain. This research uses the Systematic Literature Review methodology to collect selected research articles. The steps in defining the selected article use PRISMA. Keywords used for article search are ('Trigger' OR 'Driving') AND 'Factors' AND 'Constraints' AND ('Supply Chain' OR 'SC') AND (' electronics supply chain' OR 'e-supply chain') AND 'Processes'. Source of data used includes: Elsevier, ACM Digital Library, Emerald Insight, IEEE Explore, Inder science publisher, and Springer. Based on the literature review that was carried out, the resulting trigger factors in the e-supply chain, including: Integrated supply chain system, IT Support, Service quality;while the constraints include: A supply chain network cyber attack, Manufacturing, storage or distribution problems, Operational, economic, environmental and social factors, Restrictive government regulations, Costs and logistics performance, cost of raw materials, Post-harvest waste, Global / digital markets, product life cycles, consumer demand, Logistics strategy, Global competitiveness, Internationalization of markets and climate change. © 2018 IEEE.

关键词： Supply chains

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Large language models for diabetes training:a prospective study

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Science Bulletin 2025年第6期70卷 934-942页

作者： Haoxuan Li Zehua Jiang Zhouyu Guan Yuqian Bao Yuexing Liu Tingting Hu Jiajia Li Ruhan Liu Liang Wu Di Cheng Hongwei Ji Yong Wang Ya-Xing Wang Carol Y.Cheung Yingfeng Zheng Jihong Wang Zhen Li Weibing Wu Cynthia Ciwei Lim Yong Mong Bee Hong Chang Tan Elif I.Ekinci David C.Klonoff Justin B.Echouffo-Tcheugui Nestoras Mathioudakis Leonor Corsino Rafael Simó Charumathi Sabanayagam Gavin Siew Wei Tan Ching-Yu Cheng Tien Yin Wong Huating Li Chun Cai Lijuan Mao Lee-Ling Lim Yih-Chung Tham Bin Sheng Weiping Jia Shanghai University of Sport Shanghai 200438China School of Clinical Medicine Beijing Tsinghua Changgung HospitalTsinghua MedicineTsinghua UniversityBeijing 100084China Beijing Visual Science and Translational Eye Research Institute(BERI) Tsinghua MedicineTsinghua UniversityBeijing 100084China Shanghai Belt and Road International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases Department of Computer Science and EngineeringSchool of ElectronicInformationand Electrical EngineeringShanghai Jiao Tong UniversityDepartment of Endocrinology and MetabolismShanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai Diabetes InstituteShanghai Clinical Center for DiabetesShanghai 200240China MoE Key Lab of Artificial Intelligence Artificial Intelligence InstituteShanghai Jiao Tong UniversityShanghai 200240China Department of Cardiology the Affiliated Hospital of Qingdao UniversityQingdao 266011China CEMS NCMISHCMSMADISAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematics University of Chinese Academy of SciencesChinese Academy of SciencesBeijing 100049China Key Laboratory of Systems Health Science of Zhejiang Province School of Life ScienceHangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China Beijing Institute of Ophthalmology Beijing Tongren HospitalCapital Medical UniversityBeijing Ophthalmology and Visual Sciences Key LaboratoryBeijing 100730China k.Department of Ophthalmology and Visual Sciences The Chinese University of Hong KongHong Kong 999077China State Key Laboratory of Ophthalmology Zhongshan Ophthalmic CenterSun Yat-sen UniversityGuangdong Provincial Key Laboratory of Ophthalmology and Visual ScienceGuangdong Provincial Clinical Research Center for Ocular DiseasesGuangzhou 510060China Department of Renal Medicine Singapore General HospitalSingHealth-Duke Academic Medical CentreSingapore169

Diabetes poses a considerable global health challenge,with varying levels of diabetes knowledge among healthcare professionals,highlighting the importance of diabetes *** Language Models(LLMs)provide new insights into diabetes training,but their performance in diabetes-related queries remains uncertain,especially outside the English language like *** first evaluated the performance of ten LLMs:ChatGPT-3.5,ChatGPT-4.0,Google Bard,LlaMA-7B,LlaMA2-7B,Baidu ERNIE Bot,Ali Tongyi Qianwen,MedGPT,HuatuoGPT,and Chinese LlaMA2-7B on diabetes-related queries,based on the Chinese National Certificate Examination for Primary Diabetes Care in China(NCE-CPDC)and the English Specialty Certificate Examination in Endocrinology and Diabetes of Membership of the Royal College of Physicians of the United ***,we assessed the training of primary care physicians(PCPs)without and with the assistance of ChatGPT-4.0 in the NCE-CPDC examination to ascertain the reliability of LLMs as medical *** found that ChatGPT-4.0 outperformed other LLMs in the English examination,achieving a passing accuracy of 62.50%,which was significantly higher than that of Google Bard,LlaMA-7B,and *** the NCE-CPFC examination,ChatGPT-4.0,Ali Tongyi Qianwen,Baidu ERNIE Bot,Google Bard,MedGPT,and ChatGPT-3.5 successfully passed,whereas LlaMA2-7B,HuatuoGPT,Chinese LLaMA2-7B,and LlaMA-7B ***-4.0(84.82%)surpassed all PCPs and assisted most PCPs in the NCE-CPDC examination(improving by 1%–6.13%).In summary,LLMs demonstrated outstanding competence for diabetes-related questions in both the Chinese and English language,and hold great potential to assist future diabetes training for physicians globally.

关键词： Diabetes Diabetestraining Largelanguagemodels Primarydiabetescare Prospectivestudy

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