浅谈基于大型语言模型的聊天机器人对医学教育的影响
收稿日期: 2023-07-18
网络出版日期: 2024-03-18
基金资助
国家自然科学基金项目(82270383);国家自然科学基金项目(82000368)
Discussion on the influence of chatbot based on large-scale language model on medical education
潘柔百, 陶蓉 . 浅谈基于大型语言模型的聊天机器人对医学教育的影响[J]. 内科理论与实践, 2023 , 18(06) : 439 -446 . DOI: 10.16138/j.1673-6087.2023.06.012
| [1] | Kaul V, Enslin S, Gross SA. History of artificial intelligence in medicine[J]. Gastrointest Endosc, 2020, 92(4): 807-812. |
| [2] | Gilson A, Safranek CW, Huang T, et al. How does ChatGPT perform on the United States medical licensing examination? The implications of large language models for medical education and knowledge assessment[J]. JMIR Med Educ, 2023, 9: e45312. |
| [3] | Kung TH, Cheatham M, Medenilla A, et al. Performance of ChatGPT on USMLE: potential for AI-assisted medical education using large language models[J]. PLOS Digit Health, 2023, 2(2): e0000198. |
| [4] | Manohar N, Prasad SS. Use of ChatGPT in academic publishing: a rare case of seronegative systemic lupus erythematosus in a patient with HIV infection[J]. Cureus, 2023, 15(2): e34616. |
| [5] | Wang J, Deng H, Liu B, et al. Systematic evaluation of research progress on natural language processing in medicine over the past 20 years: bibliometric study on PubMed[J]. J Med Internet Res, 2020, 22(1): e16816. |
| [6] | Sarker A, Klein A Z, Mee J, et al. An interpretable natural language processing system for written medical examination assessment[J]. J Biomed Inform, 2019, 98: 103268. |
| [7] | Booth GJ, Ross B, Cronin WA, et al. Competency-based assessments: leveraging artificial intelligence to predict subcompetency content[J]. Acad Med, 2023, 98(4): 497-504. |
| [8] | Zack T, Dualiwal G, Geha R, et al. A clinical reasoning-encoded case library developed through natural language processing[J]. J Gen Intern Med, 2023, 38(1): 5-11. |
| [9] | Mellia JA, Basta MN, Toyoda Y, et al. Natural language processing in surgery: a systematic review and meta-analysis[J]. Ann Surg, 2021, 273(5): 900-908. |
| [10] | Goulart BHL, Silgard ET, Baik CS, et al. Validity of natural language processing for ascertainment of EGFR and ALK test results in SEER cases of stage Ⅳ non-small-cell lung cancer[J]. JCO Clin Cancer Inform, 2019, 3: 1-15. |
| [11] | Sorin V, Barash Y, Konen E, et al. Deep-learning natural language processing for oncological applications[J]. Lancet Oncol, 2020, 21(12): 1553-1556. |
| [12] | Kehl KL, Elarakeby H, Nishino M, et al. Assessment of deep natural language processing in ascertaining oncologic outcomes from radiology reports[J]. JAMA Oncol, 2019, 5(10): 1421-1429. |
| [13] | Vaswani A, Shazeer N, Parmar N, et al. Attention is all you need[C]// Advances in neural information processing systems, 2017: 5998-6008. |
| [14] | Radford A, Narasimhan K, Salimans T, et al. Improving language understanding by generative pre-training[EB/OL]. 2018. https://www.cs.ubc.ca/-amuham01/LING530/papers/radford2018improving.pdf. |
| [15] | Brown TB, Mann B, Amodel D. Language models are few-shot learners[EB/OL]. 2020. https://www.semanticscholar.org/paper/Language-Models-are-Few-Shot-Learners-Brown-Mann/6b85b63579a916f705a8e10a49bd8d849d91b1fc. |
| [16] | Ouyang L, Wu J, Jiang X, et al. Training language models to follow instructions with human feedback[EB /OL]. 2022. https://cdn.openai.com/papers/Training_language_models_to_follow_instructions_with_human_feedback.pdf. |
| [17] | Kaur A, Singh S, Chandan JS, et al. Qualitative exploration of digital chatbot use in medical education[J]. Digit Health, 2021, 7: 20552076211038151. |
| [18] | Al Kahf S, Roche A, Baron A, et al. Chatbot-based serious games: a useful tool for training medical students?[J]. PLoS One, 2023, 18(3): e0278673. |
| [19] | Lee J, Kim H, Kim KH, et al. Effective virtual patient simulators for medical communication training[J]. Med Educ, 2020, 54(9): 786-795. |
| [20] | Strong E, Digiammarino A, Weng Y, et al. Chatbot vs medical student performance on free-response clinical reasoning examinations[J]. JAMA Intern Med, 2023, 183(9): 1028-1030. |
| [21] | Reese L, Quinn PJ, Davies B, et al. How does peer teaching compare to faculty teaching? A systematic review and meta-analysis[J]. Med Teach, 2016, 38(8): 829-837. |
| [22] | Else H. Abstracts written by ChatGPT fool scientists[J]. Nature, 2023, 613(7944): 423. |
| [23] | Obermeyer Z, Powers B, Vogeli C, et al. Dissecting racial bias in an algorithm used to manage the health of populations[J]. Science, 2019, 366(6464): 447-453. |
| [24] | Wang X, Gong Z, Wang G, et al. ChatGPT performs on the Chinese national medical licensing examination[J]. J Med Syst, 2023, 47(1): 86. |
| [25] | Kuhail MA, Alturki N, Alramlawi S, et al. Interacting with educational chatbots[J]. Educ Inf Technol (Dordr), 2023, 28(1): 973-1018. |
| [26] | Tlili A, Shehata B, Adarkwah MA, et al. What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education[J]. Smart Learning Environments, 2023, 10(1): 15. |
| [27] | Gao CA, Howard FM, Markov NS, et al. Comparing scientific abstracts generated by ChatGPT to real abstracts with detectors and blinded human reviewers[J]. NPJ Digit Med, 2023, 6(1): 75. |
| [28] | Bhatia G, Kulkarni A. ChatGPT as co-author: are researchers impressed or distressed?[J]. Asian J Psychiatr, 2023, 84: 103564. |
| [29] | Stokel-Walker C. ChatGPT listed as author on research papers: many scientists disapprove[J]. Nature, 2023, 613(7945): 620-621. |
| [30] | Anderson N, Belavy DL, Perle SM, et al. AI did not write this manuscript, or did it? Can we trick the AI text detector into generated texts? The potential future of ChatGPT and AI in Sports & Exercise Medicine manuscript generation[J]. BMJ Open Sport Exerc Med, 2023, 9(1): e001568. |
| [31] | King MR, ChatGPT. A conversation on artificial intelligence, chatbots, and plagiarism in higher education[J]. Cell Mol Bioeng, 2023, 16(1): 1-2. |
| [32] | Skjuve M, F?lstad A, Fostervold KI, et al. A longitudinal study of human-chatbot relationships[J]. International Journal of Human-Computer Studies, 2022, 168: 102903. |
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