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Large language models for diabetes care: Potentials and prospects
基于大语言模型的糖尿病管理:潜力与展望

查看参考文献16篇

Sheng Bin 1   Guan Zhouyu 1   Lim Lee Ling 2,3,4   Jiang Zehua 5,6   Mathioudakis Nestoras 7   Li Jiajia 1   Liu Ruhan 1   Bao Yuqian 1   Bee Yong Mong 8   Wang Yaxing 9   Zheng Yingfeng 10   Tan Gavin Siew Wei 11   Ji Hongwei 12   Car Josip 13,14   Wang Haibo 15 *   Klonoff David C 16 *   Li Huating 1 *   Tham Yih Chung 11,17,18,19 *   Wong Tien Yin 5,6,11 *   Jia Weiping 1 *  
文摘 The increasing prevalence of diabetes has become a global public health concern in the 21st century. In 2021, it was estimated that 537 million people had diabetes, and this number is projected to reach 643 million by 2030, and 783 million by 2045 [1]. Such a huge burden of diabetes brings great challenges in its prevention and management, including early diagnosis, timely interventions, and regular monitoring of risk factor control and complications screening. Continuous self-care support and patient empowerment can enhance clinical and psychobehavioural outcomes [2], although these require additional resources including manpower, infrastructure (hard and technology), and finances. The emergence of digital health technologies (DHTs), especially artificial intelligence (AI), may help address these obstacles and alleviate the burden of diabetes [3]. Large language models (LLMs), a generative AI that can accept image and text inputs and produce text outputs, have shown promise in various aspects of medical care.
来源 Science Bulletin ,2024,69(5):583-588 【核心库】
DOI 10.1016/j.scib.2024.01.004
地址

1. Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong Uni, Shanghai International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases, Shanghai, 200240  

2. Department of Medicine, Faculty of Medicine, University of Malaya, Malaysia, Kuala Lumpur, 50603  

3. Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong  

4. Asia Diabetes Foundation, Hong Kong  

5. Tsinghua Medicine of Tsinghua University, Beijing, 100084  

6. School of Clinical Medicine, Beijing Tsinghua Changgung Hospital, Beijing, 102218  

7. Division of Endocrinology, Diabetes, & Metabolism, Johns Hopkins University School of Medicine, USA, Baltimore, 21211  

8. Department of Endocrinology, Singapore General Hospital, Singapore, Singapore, 169608  

9. Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Capital University of Medical Science, Beijing Ophthalmology and Visual Sciences Key Laboratory, Beijing, 100730  

10. Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, State Key Laboratory of Ophthalmology, Guangzhou, 510060  

11. Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore, 168751  

12. Department of Cardiology, the Affiliated Hospital of Qingdao University, Qingdao, 266011  

13. Centre for Population Health Sciences, Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore, 639798  

14. Department of Primary Care and Public Health, School of Public Health, Imperial College London, UK, London, SW7 2BU  

15. Clinical Trial Unit, Research Centre of Big Data and Artificial Intelligence in Medicine, Institute of Precision Medicine, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510080  

16. Diabetes Research Institute, Mills-Peninsula Medical Center, USA, San Mateo, 94010  

17. Centre for Innovation and Precision Eye Health, National University of Singapore, Singapore, Singapore, 119077  

18. Department of Ophthalmology, National University of Singapore, Singapore, Singapore, 119077  

19. Ophthalmology and Visual Science Academic Cli, Singapore, Singapore, 169857

语种 英文
文献类型 研究性论文
ISSN 2095-9273
学科 内科学
基金 supported by the National Key R&D Program of China ;  国家自然科学基金 ;  the Shanghai Municipal Key Clinical Specialty, Shanghai Research Center for Endocrine and Metabolic Diseases ;  the Chinese Academy of Engineering ;  the Innovative Research Team of High-level Local Universities in Shanghai
文献收藏号 CSCD:7728582

参考文献 共 16 共1页

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