首页 > 过刊浏览>2023年第44卷第7期 >以ChatGPT为代表的大语言模型在临床医学中的应用综述
PDF HTML阅读 XML下载 导出引用 引用提醒
以ChatGPT为代表的大语言模型在临床医学中的应用综述
作者:
作者单位:

(1.神州医疗科技股份有限公司 北京 100080;2.南方医科大学卫生与健康管理研究所 广州 510515;3. 南方医科大学南方医院赣州医院 赣州 341099;4.空军军医大学唐都医院 西安 710038;5. .南方医科大学南方医院 广州 510515)

作者简介:

马武仁,医学数据分析师,发表论文10余篇；通信作者:史文钊,硕士。

中图分类号:

R-058

基金项目:

国家重点研发计划项目(项目编号:2020 YFC2006400)。


A Comprehensive Review of the Applications of Large Language Models in Clinical Medicine with ChatGPT as a Representative
Author:
Affiliation:

(1.Digital China Health Technologies Corporation Limited, Beijing 100080, China;2.Institute of Health Management, Southern Medical University, Guangzhou 510515, China; 3.Ganzhou Hospital-Nanfang Hospital, Southern Medical University, Ganzhou 341099, China; 4.Tangdu Hospital, The Airforce Military Medical University, Xi〖DK〗’an 710038, China; 5.Nanfang Hospital, Southern Medical University, Guangzhou 510515, China)

  • 摘要
  • 访问统计
  • 参考文献 [1]
  • 引证文献
  • 文章评论
    摘要:

    目的/意义 近年来大语言模型技术飞速发展,其在临床中的应用亟待总结分析。方法/过程 在相关文献分析基础上,梳理以ChatGPT为代表的大语言模型在临床问诊、病史采集及文本撰写、临床辅助决策、个性化精准医疗、医患沟通及患者心理支持、学术研究、医学教育、医院管理等临床领域的应用情况。结果/结论 大语言模型具备全面颠覆医疗生态圈的潜力,虽然面临诸多挑战,但终将造福医患。

    Abstract:

    Purpose/Significance In recent years, the technology of large language models has been rapidly advancing, and their applications in clinical settings urgently need to be summarized and analyzed. Method/Process Based on a review of relevant literatures, the paper outlines the applications of large language models, represented by ChatGPT, in various clinical fields such as clinical consultation, medical history collection and text writing, clinical decision support, personalized precision medicine, doctor-patient communication and patient psychological support, academic research, medical education, and hospital management. Result/Conclusion Large language models have the potential to completely revolutionize the healthcare ecosystem, despite facing numerous challenges, they will ultimately benefit both doctors and patients.

    参考文献
    1 MANNING C D.Human language understanding & reasoning [J].Daedalus, 2022,151(2):127-138.2 MANN D L.Artificial intelligence discusses the role of artificial intelligence in translational medicine:a JACC:basic to translational science interview with ChatGPT [J].Basic to translational science, 2023,8(2):221-223.3 ZHOU C, LI Q, LI C, et al.A comprehensive survey on pretrained foundation models:a history from bert to chatgpt[EB/OL].[2023-06-11].https://arxiv.org/abs/2302.09419.4 XIA C S, ZHANG L.Conversational automated program repair [EB/OL].[2023-06-09].https://arxiv.org/abs/2301.13246.5 ZHENG O, ABDEL-ATY M, WANG D, et al.ChatGPT is on the horizon:could a large language model be all we need for intelligent transportation[EB/OL].[2023-06-06].https://arxiv.org/abs/2303.05382.6 OUYANG L, WU J, JIANG X, et al.Training language models to follow instructions with human feedback [EB/OL].[2023-06-11].https://arxiv.org/abs/2203.02155.7 YE S, HWANG H, YANG S, et al.In-context instruction learning[EB/OL].[2023-06-07].https://arxiv.org/abs/2302.14691.8 KUNG T H, CHEATHAM M, MEDENILLA A, et al.Performance of ChatGPT on USMLE:potential for AI-assisted medical education using large language models [J].PLOS digital health, 2023,2(2):e198.9 PubMedQA.PubMedQA:a dataset for biomedical research question answering[EB/OL].[2023-04-01].https://pubmedqa.github.io/.10 SINGHAL K, AZIZI S, TU T, et al.Large language models encode clinical knowledge[EB/OL].[2023-07-18].https://www.nature.com/articles/s41586-023-06291-2#citeas.11 DELIBERATO R O, CELI L A, STONE D J.Clinical note creation, binning, and artificial intelligence [J].JMIR medical informatics, 2017,5(3):e7627.12 JOUKES E, ABU-HANNA A, CORNET R, et al.Time spent on dedicated patient care and documentation tasks before and after the introduction of a structured and standardized electronic health record [J].Applied clinical informatics, 2018,9(1):46-53.13 FRIEDBERG M W, CHEN P G, VAN BUSUM K R, et al.Factors affecting physician professional satisfaction and their implications for patient care, health systems, and health policy [J].Rand health quarterly, 2014,3(4):1.14 WACHTER R, GOLDSMITH J.To combat physician burnout and improve care, fix the electronic health record[EB/OL].[2023-06-10].https://hbr.org/2018/03/to-combat-physician-burnout-and-improve-care-fix-the-electronic-health-record.15 CAMPBELL E M, SITTIG D F, ASH J S, et al.Types of unintended consequences related to computerized provider order entry [J].Journal of the American medical informatics association, 2006,13(5):547-556.16 KLANN J G, SZOLOVITS P.An intelligent listening framework for capturing encounter notes from a doctor-patient dialog [J].BMC medical informatics and decision making, 2009,9(S1):1-10.17 DIGIORGIO A M, EHRENFELD J M.Artificial intelligence in medicine & ChatGPT:de-tether the physician [J].Journal of medical systems, 2023,47(1):32.18 EARNSHAW C H, PEDERSEN A, EVANS J, et al.Improving the quality of discharge summaries through a direct feedback system[J].Future healthcare journal, 2020,7(2):149.19 PATEL S B, LAM K.ChatGPT:the future of discharge summaries[J].The lancet digital health, 2023,5(3):e107-e108.20 FATANI B.ChatGPT for future medical and dental research [J].Cureus, 2023,15(4):e37285.21 CADAMURO J, CABITZA F, DEBELJAK Z, et al.Potentials and pitfalls of ChatGPT and natural-language artificial intelligence models for the understanding of laboratory medicine test results.An assessment by the European federation of clinical chemistry and laboratory medicine (EFLM) working group on artificial intelligence (WG-AI) [J].Clinical chemistry and laboratory medicine, 2023,61(7):1158-1166.22 BISWAS S S.Role of ChatGPT in radiology with a focus on pediatric radiology:proof by examples [J].Pediatric radiology, 2023,53(5):818-822.23 HU M, PAN S, LI Y, et al.Advancing medical imaging with language models:a journey from n-grams to ChatGPT[EB/OL].[2023-06-02].https://arxiv.org/abs/2304.04920.24 HARSKAMP R E, DE CLERCQ L.Performance of ChatGPT as an AI-assisted decision support tool in medicine:a proof-of-concept study for interpreting symptoms and management of common cardiac conditions (AMSTELHEART-2) [EB/OL].[2023-05-18].https://www.medrxiv.org/content/10.1101/2023.03.25.23285475v1.25 AGBAVOR F, LIANG H.Predicting dementia from spontaneous speech using large language models [J].PLOS digital health, 2022,1(12):e168.26 RAO A S, KIM J, KAMINENI M, et al.Evaluating ChatGPT as an adjunct for radiologic decision-making [EB/OL].[2023-06-10].https://www.medrxiv.org/content/10.1101/2023.02.02.23285399v1.27 RAO A S, PANG M, KIM J, et al.Assessing the utility of ChatGPT throughout the entire clinical workflow [EB/OL].[2023-05-23].https://pubmed.ncbi.nlm.nih.gov/36865204/.28 LIU S, WRIGHT A P, PATTERSON B L, et al.Assessing the value of ChatGPT for clinical decision support optimization [EB/OL].[2023-05-29].https://pubmed.nc-bi.nlm.nih.gov/36865144/.29 CHENG K, SUN Z, HE Y, et al.The potential impact of ChatGPT/GPT-4 on surgery:will it topple the profession of surgeons[J].International journal of surgery, 2023,109(5):1545-1547.30 HUANG Y, GOMAA A, WEISSMANN T, et al.Benchmarking ChatGPT-4 on ACR radiation oncology in-training exam (TXIT):potentials and challenges for AI-assisted medical education and decision making in radiation oncology [EB/OL].[2023-06-15].https://arxiv.org/abs/2304.11957.31 HOPKINS A M, LOGAN J M, KICHENADASSE G, et al.Artificial intelligence chatbots will revolutionize how cancer patients access information:ChatGPT represents a paradigm-shift [J].JNCI cancer spectrum, 2023,7(2):10.32 JAVAID M, HALEEM A, SINGH R P.ChatGPT for healthcare services:an emerging stage for an innovative perspective [J].BenchCouncil transactions on benchmarks, standards and evaluations, 2023,3(1):1-11.33 SALLAM M.The utility of ChatGPT as an example of large language models in healthcare education, research and practice:systematic review on the future perspectives and potential limitations [EB/OL].[2023-06-09].https://www.medrxiv.org/content/10.1101/2023.02.19.23286155v1.34 LYU Q, TAN J, ZAPADKA M E, et al.Translating radiology reports into plain language using chatgpt and gpt-4 with prompt learning:promising results, limitations, and potential [EB/OL].[2023-05-19].https://arxiv.org/abs/2303.09038.35 SALLAM M, SALIM N, BARAKAT M, et al.ChatGPT applications in medical, dental, pharmacy, and public health education:a descriptive study highlighting the advantages and limitations [J].Narra J, 2023,3(1):e103.36 ZHU L, MOU W, CHEN R.Can the ChatGPT and other large language models with internet-connected database solve the questions and concerns of patient with prostate cancer and help democratize medical knowledge [J].Journal of translational medicine, 2023,21(1):1-4.37 DEJEAN D, GIACOMINI M, VANSTONE M, et al.Patient experiences of depression and anxiety with chronic disease:a systematic review and qualitative meta-synthesis [J].Ontario health technology assessment series, 2013,13(16):1.38 ESHGHIE M, ESHGHIE M.ChatGPT as a therapist assistant:a suitability study [EB/OL].[2023-06-01].https://arxiv.org/abs/2304.09873.39 YANG K, JI S, ZHANG T, et al.On the evaluations of ChatGPT and emotion-enhanced prompting for mental health analysis[EB/OL].[2023-05-23].https://arxiv.org/abs/2304.03347.40 ARIF T B, MUNAF U, UL-HAQUE I.The future of medical education and research:is ChatGPT a blessing or blight in disguise[J].Medical education online, 2023,28(1):2181052.41 VAISHYA R, MISRA A, VAISH A.ChatGPT:is this version good for healthcare and research [J].Diabetes & metabolic syndrome:clinical research & reviews, 2023,17(4):102744.42 GAO C A, HOWARD F M, MARKOV N S, et al.Comparing scientific abstracts generated by ChatGPT to original abstracts using an artificial intelligence output detector, plagiarism detector, and blinded human reviewers [EB/OL].[2023-06-02].https://www.biorxiv.org/content/10.1101/2022.12.23.521610v1.43 OMAR R, MANGUKIYA O, KALNIS P, et al.ChatGPT versus traditional question answering for knowledge graphs:current status and future directions towards knowledge graph chatbots[EB/OL].[2023-05-27].https://arxiv.org/abs/2302.06466.44 WANG S, SCELLS H, KOOPMAN B, et al.Can ChatgPT write a good boolean query for systematic review literature search [EB/OL].[2023-05-18].https://arxiv.org/abs/2302.03495.45 LUND B D, WANG T.Chatting about ChatGPT:how may AI and GPT impact academia and libraries [J].Library hi tech news, 2023,40(3):26-29.46 MACDONALD C, ADELOYE D, SHEIKH A, et al.Can ChatGPT draft a research article? An example of population-level vaccine effectiveness analysis [J].Journal of global health, 2023,13(2):1003.47 KUMAR A H.Analysis of ChatGPT tool to assess the potential of its utility for academic writing in biomedical domain [J].Biology, engineering, medicine and science reports, 2023,9(1):24-30.48 ZHAI X.ChatGPT and AI:the game changer for education [EB/OL].[2023-05-03].https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4389098.49 CHAN K S, ZARY N.Applications and challenges of implementing artificial intelligence in medical education:integrative review[J].JMIR medical education, 2019,5(1):e13930.50 WHALLEY B, FRANCE D, PARK J, et al.Towards flexible personalized learning and the future educational system in the fourth industrial revolution in the wake of Covid-19 [J].Higher education pedagogies, 2021,6(1):79-99.51 PARANJAPE K, SCHINKEL M, PANDAY R N, et al.Introducing artificial intelligence training in medical education [J].JMIR medical education, 2019,5(2):e16048.52 TALAN T, KALINKARA Y.The role of artificial intelligence in higher education:ChatGPT assessment for anatomy course [J].Uluslararas ynetim bili瘙塂im sistemleri ve bilgisayar bilimleri dergisi, 2023,7(1):33-40.53 SEETHARAMAN R.Revolutionizing medical education:can ChatGPT boost subjective learning and expression[J].Journal of medical systems, 2023,47(1):1-4.54 BAIDOO-ANU D, OWUSU ANSAH L.Education in the era of generative artificial intelligence (AI):understanding the potential benefits of ChatGPT in promoting teaching and learning[EB/OL].[2023-06-05].https://papers.ss-rn.com/sol3/papers.cfm?abstract_id=4337484.55 LU Y, WU H, QI S, et al.Artificial intelligence in intensive care medicine:toward a ChatGPT/GPT-4 way[EB/OL].[2023-03-10].https://pubmed.ncbi.nlm.nih.gov/37179277/.56 CURY R C, MEGYERI I, LINDSEY T, et al.Natural language processing and machine learning for detection of respiratory illness by chest ct imaging and tracking of covid-19 pandemic in the united states [J].Radiology:cardiothoracic imaging, 2021,3(1):e200596.57 CHENG K, LI Z, HE Y, et al.Potential use of artificial intelligence in infectious disease:take ChatGPT as an example [J].Annals of biomedical engineering, 2023,51(6):1130-1135.58 BISWAS S.Using ChatGPT for insurance:current and prospective roles[EB/OL].[2023-05-11].https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4405394.59 JOHNSON K W, TORRES SOTO J, GLICKSBERG B S, et al.Artificial intelligence in cardiology [J].Journal of the American college of cardiology, 2018,71(23):2668-2679.60 LOPEZ K, FODEH S J, ALLAM A, et al.Reducing annotation burden through multimodal learning [J].Frontiers in big data, 2020,3(1):19.61 DASH S, SHAKYAWAR S K, SHARMA M, et al.Big data in healthcare:management, analysis and future prospects [J].Journal of big data, 2019,6(1):1-25.62 SUN T Q, MEDAGLIA R.Mapping the challenges of artificial intelligence in the public sector:evidence from public healthcare[J].Government information quarterly, 2019,36(2):368-383.63 KILOVATY I.Psychological data breach harms [J].North Carolina journal of law & technology, 2021,23(1):1-65.64 WIENS J, SHENOY E S.Machine learning for healthcare:on the verge of a major shift in healthcare epidemiology [J].Clinical infectious diseases, 2018,66(1):149-153.65 WANG F, KAUSHAL R, KHULLAR D.Should health care demand interpretable artificial intelligence or accept “black box” medicine[J].Annals of internal medicine, 2020,172(1):59-60.66 WILSON A, SAEED H, PRINGLE C, et al.Artificial intelligence projects in healthcare:10 practical tips for success in a clinical environment [J].BMJ health & care informatics, 2021,28(1):e100323.67 DAVAHLI M R, KARWOWSKI W, FIOK K, et al.Controlling safety of artificial intelligence-based systems in healthcare [J].Symmetry, 2021,13(1):102.68 MORRISON K.Artificial intelligence and the NHS:a qualitative exploration of the factors influencing adoption [J].Future healthcare journal, 2021,8(3):e648.
    相似文献
    引证文献
    网友评论
    网友评论
    分享到微博
    发 布
引用本文

马武仁,弓孟春,戴辉,等.以ChatGPT为代表的大语言模型在临床医学中的应用综述[J].医学信息学杂志,2023,44(7):9-17

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 最后修改日期:2023-07-18
  • 在线发布日期: 2023-08-29

友情链接

联系地址：北京市朝阳区雅宝路3号     邮编：100020

联系电话：（010）52328686/87     邮箱：yxxxx@imicams.ac.cn

技术支持：北京勤云科技发展有限公司 京ICP备10218182-2

京公网安备 11010502037823号

总访问量：6114403 今日访问量：936

《医学信息学杂志》

微信公众号

扫码关注

官方微信