
Journal of Frontiers of Computer Science and Technology ›› 2025, Vol. 19 ›› Issue (8): 2043-2056.DOI: 10.3778/j.issn.1673-9418.2409076
• Frontiers·Surveys • Previous Articles Next Articles
TIAN Chongteng, LIU Jing, WANG Xiaoyan, LI Ming
Online:2025-08-01
Published:2025-07-31
田崇腾,刘静,王晓燕,李明
TIAN Chongteng, LIU Jing, WANG Xiaoyan, LI Ming. Review of Application of Large Language Models GPT in Medical Text[J]. Journal of Frontiers of Computer Science and Technology, 2025, 19(8): 2043-2056.
田崇腾, 刘静, 王晓燕, 李明. 大语言模型GPT在医疗文本中的应用综述[J]. 计算机科学与探索, 2025, 19(8): 2043-2056.
Add to citation manager EndNote|Ris|BibTeX
URL: http://fcst.ceaj.org/EN/10.3778/j.issn.1673-9418.2409076
| [1] MOOR M, BANERJEE O, ABAD Z S H, et al. Foundation models for generalist medical artificial intelligence[J]. Nature, 2023, 616(7956): 259-265. [2] CHOWDHARY K R. Natural language processing[M]// Fundamentals of artificial intelligence. New Delhi: Springer India, 2020: 603-649. [3] THIRUNAVUKARASU A J, TING D S J, ELANGOVAN K, et al. Large language models in medicine[J]. Nature Medicine, 2023, 29(8): 1930-1940. [4] LECUN Y, BENGIO Y, HINTON G. Deep learning[J]. Nature, 2015, 521(7553): 436-444. [5] SAMEK W, MONTAVON G, LAPUSCHKIN S, et al. Explaining deep neural networks and beyond: a review of methods and applications[J]. Proceedings of the IEEE, 2021, 109(3): 247-278. [6] ZENG W, REN X Z, SU T, et al. PanGu-α: large-scale autoregressive pretrained Chinese language models with auto-parallel computation[EB/OL]. [2024-07-19]. https://arxiv.org/ abs/2104.12369. [7] MANN D L. Artificial intelligence discusses the role of artificial intelligence in translational medicine: a JACC: basic to translational science interview with ChatGPT[J]. JACC Basic to Translational Science, 2023, 8(2): 221-223. [8] TEAM G, ANIL R, BORGEAUD S, et al. Gemini: a family of highly capable multimodal models[EB/OL]. [2024-07-19]. https://arxiv.org/abs/2312.11805. [9] KELLY D, CHEN Y M, CORNWELL S E, et al. Bing chat: the future of search engines?[J]. Proceedings of the Association for Information Science and Technology, 2023, 60(1): 1007-1009. [10] 孔祥溢, 王任直. 人工智能及在医疗领域的应用[J]. 医学信息学杂志, 2016, 37(11): 2-5. KONG X Y, WANG R Z. Artificial intelligence and its application in medical field[J]. Journal of Medical Informatics, 2016, 37(11): 2-5. [11] HAUPT C E, MARKS M. AI-generated medical advice-GPT and beyond[J]. JAMA, 2023, 329(16): 1349-1350. [12] LANDSCHAFT A, ANTWEILER D, MACKAY S, et al. Implementation and evaluation of an additional GPT-4-based reviewer in PRISMA-based medical systematic literature reviews[J]. International Journal of Medical Informatics, 2024, 189: 105531. [13] WANG H Y, WU W Z, DOU Z, et al. Performance and exploration of ChatGPT in medical examination, records and education in Chinese: pave the way for medical AI[J]. International Journal of Medical Informatics, 2023, 177: 105173. [14] VASWANI A, SHAZEER N, PARMAR N, et al. Attention is all you need[C]//Advances in Neural Information Processing Systems 30, 2017: 5998-6008. [15] BUBECK S, CHANDRASEKARAN V, ELDAN R, et al. Sparks of artificial general intelligence: early experiments with GPT-4[EB/OL]. [2024-07-19]. https://arxiv.org/abs/2303. 12712. [16] CARVALKO J. GPT-a paradigm shift for the twenty-first century[EB/OL]. [2024-07-19]. https://www.techrxiv.org/doi/ full/10.36227/techrxiv.23690874. [17] KNOX W B, STONE P. Augmenting reinforcement learning with human feedback[C]//Proceedings of the ICML Workshop on New Developments in Imitation Learning, 2011. [18] DAI D M, SUN Y T, DONG L, et al. Why can GPT learn in-context? Language models implicitly perform gradient descent as meta-optimizers[EB/OL]. [2024-07-19]. https://arxiv.org/abs/2212.10559. [19] KNOX W B, STONE P. Interactively shaping agents via human reinforcement: the TAMER framework[C]//Proceedings of the 5th International Conference on Knowledge Capture. New York: ACM, 2009: 9-16. [20] LEIKE J, KRUEGER D, EVERITT T, et al. Scalable agent alignment via reward modeling: a research direction[EB/OL]. [2024-07-20]. https://arxiv.org/abs/1811.07871. [21] SCHULMAN J, WOLSKI F, DHARIWAL P, et al. Proximal policy optimization algorithms[EB/OL]. [2024-07-20]. https:// arxiv.org/abs/1707.06347. [22] YUAN D, RASTOGI E, NAIK G, et al. A continued pretrained LLM approach for automatic medical note generation[EB/OL]. [2024-07-20]. https://arxiv.org/abs/2403.09057. [23] GE W D, RICE H J, SHEIKH I S, et al. Improving neurology clinical care with natural language processing tools[J]. Neurology, 2023, 101(22): 1010-1018. [24] SIRRIANNI J, SEZGIN E, CLAMAN D, et al. Medical text prediction and suggestion using generative pretrained transformer models with dental medical notes[J]. Methods of Information in Medicine, 2022, 61(5/6): 195-200. [25] WAISBERG E, ONG J, MASALKHI M, et al. GPT-4: a new era of artificial intelligence in medicine[J]. Irish Journal of Medical Science (1971-), 2023, 192(6): 3197-3200. [26] CHEN L, LI H, SU Y Q, et al. Using a google web search analysis to assess the utility of ChatGPT in stem cell therapy[J]. Stem Cells Translational Medicine, 2024, 13(1): 60-68. [27] WU Z L, HASAN A, WU J G, et al. Chain-of-though (CoT) prompting strategies for medical error detection and correction[EB/OL]. [2024-07-20]. https://arxiv.org/abs/2406.09103. [28] GUAN Z H, WU Z H, LIU Z L, et al. CohortGPT: an enhanced GPT for participant recruitment in clinical study[EB/OL]. [2024-07-20]. https://arxiv.org/abs/2307.11346. [29] BALKUS S V, YAN D H. Improving short text classification with augmented data using GPT-3[J]. Natural Language Engineering, 2024, 30(5): 943-972. [30] WADA A, AKASHI T, SHIH G, et al. Optimizing GPT-4 turbo diagnostic accuracy in neuroradiology through prompt engineering and confidence thresholds[J]. Diagnostics, 2024, 14(14): 1541. [31] GIUFFRè M, MASUTTI F, GULOTTA M, et al. Optimizing AI performance for autoimmune hepatitis guidelines: a case study on enhanced GPT model accuracy[J]. Digestive and Liver Disease, 2024, 56: S28. [32] SALVAGNO M, TACCONE F S, GERLI A G. Artificial intelligence hallucinations[J]. Critical Care, 2023, 27(1): 180. [33] LEE P, BUBECK S, PETRO J. Benefits, limits, and risks of GPT-4 as an AI chatbot for medicine[J]. New England Journal of Medicine, 2023, 388(13): 1233-1239. [34] CHELLI M, DESCAMPS J, LAVOUé V, et al. Hallucination rates and reference accuracy of ChatGPT and bard for systematic reviews: comparative analysis[J]. Journal of Medical Internet Research, 2024, 26: e53164. [35] SOVRANO F, ASHLEY K, BACCHELLI A. Toward eliminating hallucinations: GPT-based explanatory AI for intelligent textbooks and documentation[C]//CEUR Workshop Proceedings, 2023: 54-65. [36] SHAKIL H, ORTIZ Z, FORBES G C. Utilizing GPT to enhance text summarization: a strategy to minimize hallucinations[EB/OL]. [2024-07-20]. https://arxiv.org/abs/2405. 04039. [37] JAHANBAKHSH K, HAJIABADI M, GAGRANI V, et al. Beyond hallucination: building a reliable question answering & explanation system with GPTs[C]//Proceedings of the NeurIPS??23 Workshop on Generative AI for Education, 2023. [38] AYERS J W, POLIAK A, DREDZE M, et al. Comparing physician and artificial intelligence chatbot responses to patient questions posted to a public social media forum[J]. JAMA Internal Medicine, 2023, 183(6): 589-596. [39] GORDON E B, TOWBIN A J, WINGROVE P, et al. Enhancing patient communication with Chat-GPT in radiology: evaluating the efficacy and readability of answers to common imaging-related questions[J]. Journal of the American College of Radiology, 2024, 21(2): 353-359. [40] LIU X, ZHENG Y, DU Z, et al. GPT understands, too[EB/OL]. [2024-07-20]. https://arxiv.org/abs/2103.10385. [41] LEE T C, STALLER K, BOTOMAN V, et al. ChatGPT answers common patient questions about colonoscopy[J]. Gastroenterology, 2023, 165(2): 509-511. [42] LIU Z L, HUANG Y, YU X W, et al. DeID-GPT: zero-shot medical text de-identification by GPT-4[EB/OL]. [2024-07-20]. https://arxiv.org/abs/2303.11032. [43] ZENG C K, HE D B, FENG Q, et al. SecureGPT: a framework for multi-party privacy-preserving transformer inference in GPT[J]. IEEE Transactions on Information Forensics and Security, 2024, 19: 9480-9493. [44] LEVKOVICH I, ELYOSEPH Z. Suicide risk assessments through the eyes of ChatGPT-3.5 versus ChatGPT-4: vignette study[J]. JMIR Mental Health, 2023, 10: e51232. [45] HADAR-SHOVAL D, ELYOSEPH Z, LVOVSKY M. The plasticity of ChatGPT??s mentalizing abilities: personalization for personality structures[J]. Frontiers in Psychiatry, 2023, 14: 1234397. [46] PARKER G, SPOELMA M J. A chat about bipolar disorder[J]. Bipolar Disorders, 2024, 26(3): 249. [47] 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): e0000198. [48] GILSON A, SAFRANEK C W, HUANG T, et al. How does ChatGPT perform on the United States medical licensing examination (USMLE)? The implications of large language models for medical education and knowledge assessment[J]. JMIR Medical Education, 2023, 9: e45312. [49] JOHNSON D, GOODMAN R, PATRINELY J, et al. Assessing the accuracy and reliability of AI-generated medical responses: an evaluation of the Chat-GPT model[EB/OL]. [2024-07-20]. https://pmc.ncbi.nlm.nih.gov/articles/PMC10002821/. [50] HUANG X, ESTAU D, LIU X, et al. Evaluating the performance of ChatGPT in clinical pharmacy: a comparative study of ChatGPT and clinical pharmacists[J]. British Journal of Clinical Pharmacology, 2024, 90(1): 232-238. [51] SUáREZ A, DíAZ-FLORES GARCíA V, ALGAR J, et al. Unveiling the ChatGPT phenomenon: evaluating the consistency and accuracy of endodontic question answers[J]. International Endodontic Journal, 2024, 57(1): 108-113. [52] LAI U H, WU K S, HSU T Y, et al. Evaluating the performance of ChatGPT-4 on the United Kingdom medical licensing assessment[J]. Frontiers in Medicine, 2023, 10: 1240915. [53] TACK A, PIECH C. The AI teacher test: measuring the pedagogical ability of blender and GPT-3 in educational dialogues[EB/OL]. [2024-07-20]. https://arxiv.org/abs/2205.07540. [54] AMIN M Y M. AI and chat GPT in language teaching: enhancing EFL classroom support and transforming assessment techniques[J]. International Journal of Higher Education Pedagogies, 2023, 4(4): 1-15. [55] WANG J D, YAO Z H, YANG Z C, et al. NoteChat: a dataset of synthetic doctor-patient conversations conditioned on clinical notes[EB/OL]. [2024-07-20]. https://arxiv.org/abs/2310.15959. [56] BEN ABACHA A, YIM W W, ADAMS G, et al. Overview of the MEDIQA-chat 2023 shared tasks on the summarization & generation of doctor-patient conversations[C]//Proceedings of the 5th Clinical Natural Language Processing Workshop. Stroudsburg: ACL, 2023: 503-513. [57] RHODES G A, HUANG S H. Augmented and virtual reality in the world of GPT text and image creations: AI, metaverse, and art[M]//Augmented and virtual reality in the metaverse. Cham: Springer, 2024: 227-246. [58] 袁方, 任海玲, 赵梦, 等. 我国传染病预警监测模型研究进展综述[J]. 价值工程, 2023, 42(33): 162-165. YUAN F, REN H L, ZHAO M, et al. Review of research progress on early warning and monitoring models for infectious diseases in China[J]. Value Engineering, 2023, 42(33): 162-165. [59] HASNAIN M. ChatGPT applications and challenges in controlling monkey pox in Pakistan[J]. Annals of Biomedical Engineering, 2023, 51(9): 1889-1891. [60] HOWARD A, HOPE W, GERADA A. ChatGPT and antimicrobial advice: the end of the consulting infection doctor?[J]. The Lancet Infectious Diseases, 2023, 23(4): 405-406. [61] PEREYRA L, SCHLOTTMANN F, STEINBERG L, et al. Colorectal cancer prevention: is chat generative pretrained transformer (Chat GPT) ready to assist physicians in determining appropriate screening and surveillance recommendations?[J]. Journal of Clinical Gastroenterology, 2024, 58(10): 1022-1027. [62] ARSLAN S. Exploring the potential of chat GPT in personalized obesity treatment[J]. Annals of Biomedical Engineering, 2023, 51(9): 1887-1888. [63] ZAHRA M A, AL-TAHER A, ALQUHAIDAN M, et al. The synergy of artificial intelligence and personalized medicine for the enhanced diagnosis, treatment, and prevention of disease[J]. Drug Metabolism and Personalized Therapy, 2024, 39(2): 47-58. [64] PATRINOS G P, SARHANGI N, SARRAMI B, et al. Using ChatGPT to predict the future of personalized medicine[J]. The Pharmacogenomics Journal, 2023, 23(6): 178-184. [65] WU C Y, LEI J Y, ZHENG Q Y, et al. Can GPT-4V (ision) serve medical applications? Case studies on GPT-4V for multimodal medical diagnosis[EB/OL]. [2024-07-19]. https:// arxiv.org/abs/2310.09909. [66] YANG Z, YAO Z, TASMIN M, et al. Performance of multimodal GPT-4V on USMLE with image: potential for imaging diagnostic support with explanations[EB/OL]. [2024-07-19]. https://www.medrxiv.org/content/10.1101/2023.10.26.23297629v3. [67] BRIN D, SORIN V, BARASH Y, et al. Assessing GPT-4 multimodal performance in radiological image analysis[J]. European Radiology, 2025, 35(4): 1959-1965. [68] ZAMAN K T, HASAN W U, LI J, et al. Empowering caregivers of Alzheimer??s disease and related dementias (ADRD) with a GPT-powered voice assistant: leveraging peer insights from social media[C]//Proceedings of the 2023 IEEE Symposium on Computers and Communications. Piscataway: IEEE, 2023: 1-7. [69] DAI H X, LI Y W, LIU Z L, et al. AD-AutoGPT: an autonomous GPT for Alzheimer??s disease infodemiology[EB/OL]. [2024-07-19]. https://arxiv.org/abs/2306.10095. [70] RUNDE B S, ALAPATI A, BAZAN N G. The optimization of a natural language processing approach for the automatic detection of Alzheimer??s disease using GPT embeddings[J]. Brain Sciences, 2024, 14(3): 211. [71] WU C Y, LIN Z H, FANG W L, et al. A medical diagnostic assistant based on LLM[C]//Proceedings of the 2024 China Health Information Processing Conference. Singapore: Springer, 2024: 135-147. [72] ULLAH E, PARWANI A, BAIG M M, et al. Challenges and barriers of using large language models (LLM) such as ChatGPT for diagnostic medicine with a focus on digital pathology-a recent scoping review[J]. Diagnostic Pathology, 2024, 19(1): 43. [73] SCHERBAKOV D, HUBIG N, JANSARI V, et al. The emergence of large language models (LLM) as a tool in literature reviews: an LLM automated systematic review[EB/OL]. [2024-09-22]. https://arxiv.org/abs/2409.04600. [74] HALTAUFDERHEIDE J, RANISCH R. The ethics of ChatGPT in medicine and healthcare: a systematic review on large language models (LLMs)[J]. NPJ Digital Medicine, 2024, 7: 183. [75] PENG L, LUO G X, ZHOU S C, et al. An in-depth evaluation of federated learning on biomedical natural language processing for information extraction[J]. NPJ Digital Medicine, 2024, 7: 127. [76] SONG Y P, ZHANG J H, TIAN Z L, et al. LLM-based privacy data augmentation guided by knowledge distillation with a distribution tutor for medical text classification[EB/OL]. [2024-07-20]. https://arxiv.org/abs/2402.16515. [77] MILETIC M, SARIYAR M. Assessing the potentials of LLMs and GANs as state-of-the-art tabular synthetic data generation methods[C]//Proceedings of the 2024 International Conference on Privacy in Statistical Databases. Cham: Springer, 2024: 374-389. [78] BLALOCK D, ORTIZ J J G, FRANKLE J, et al. What is the state of neural network pruning?[EB/OL]. [2024-07-20]. https://arxiv.org/abs/2003.03033. [79] SONG L, CHEN Y K, YANG S, et al. Low-rank approximation for sparse attention in multi-modal LLMs[C]//Proceedings of the 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2024: 13763-13773. [80] XU X H, LI M, TAO C Y, et al. A survey on knowledge distillation of large language models[EB/OL]. [2024-07-20]. https://arxiv.org/abs/2402.13116. [81] GOU J P, YU B S, MAYBANK S J, et al. Knowledge distillation: a survey[J]. International Journal of Computer Vision, 2021, 129(6): 1789-1819. [82] KUMAR A, NASEER M, NARAYAN S, et al. Multi-modal generation via cross-modal in-context learning[EB/OL]. [2024-07-19]. https://arxiv.org/abs/2405.18304. [83] LI Y, SONG Z C, GONG Z J, et al. Multimodal growth and development assessment model[EB/OL]. [2024-10-20]. https:// arxiv.org/abs/2410.13647. [84] LIU Y S, WU Z Q, CHEN B Z, et al. Medical cross-modal prompt hashing with robust noisy correspondence learning[C]//Proceedings of the 2024 International Conference on Medical Image Computing and Computer Assisted Intervention. Cham: Springer, 2024: 250-261. [85] WANG P Y, ZHANG H Q, YUAN Y X. MCPL: multi-modal collaborative prompt learning for medical vision-language model[J]. IEEE Transactions on Medical Imaging, 2024, 43(12): 4224-4235. [86] HUANG H Y, ZHENG O, WANG D D, et al. ChatGPT for shaping the future of dentistry: the potential of multi-modal large language model[J]. International Journal of Oral Science, 2023, 15: 29. [87] YAN Q, DUAN J W, WANG J X. Multi-modal concept alignment pre-training for generative medical visual question answering[C]//Findings of the Association for Computational Linguistics: ACL 2024. Stroudsburg: ACL, 2024: 5378-5389. |
| [1] | ZHANG Hao, LI Shiqi, DIAO Yufeng, YANG Liang, LIN Hongfei, FAN Xiaochao. Construction and Research of Multilingual Parallel Emotion Corpus [J]. Journal of Frontiers of Computer Science and Technology, 2025, 19(9): 2506-2519. |
| [2] | Anggeluma, WANG Siriguleng, SI Qintu. Overview of Research on Knowledge Graph Completion [J]. Journal of Frontiers of Computer Science and Technology, 2025, 19(9): 2302-2318. |
| [3] | ZHANG Cheng, CAO Jingxu, LYU Jinxin, YAN Dongmei. Study on Interpretability of Knowledge Distillation Based on Convex Hulls from Perspective of Natural Language [J]. Journal of Frontiers of Computer Science and Technology, 2025, 19(8): 2174-2187. |
| [4] | XIA Jianglan, LI Yanling, GE Fengpei. Survey of Entity Relation Extraction Based on Large Language Models [J]. Journal of Frontiers of Computer Science and Technology, 2025, 19(7): 1681-1698. |
| [5] | XU Guangyuan, ZHANG Yaqiang, SHI Hongzhi. Review of Fault-Tolerant Technologies for Large-Scale DNN Training Scenarios [J]. Journal of Frontiers of Computer Science and Technology, 2025, 19(7): 1771-1788. |
| [6] | ZHANG Xin, SUN Jingchao. Review of False Information Detection Frameworks Based on Large Language Models [J]. Journal of Frontiers of Computer Science and Technology, 2025, 19(6): 1414-1436. |
| [7] | XU Delong, LIN Min, WANG Yurong, ZHANG Shujun. Survey of NLP Data Augmentation Methods Based on Large Language Models [J]. Journal of Frontiers of Computer Science and Technology, 2025, 19(6): 1395-1413. |
| [8] | LI Juhao, SHI Lei, DING Meng, LEI Yongsheng, ZHAO Dongyue, CHEN Long. Social Media Text Stance Detection Based on Large Language Models [J]. Journal of Frontiers of Computer Science and Technology, 2025, 19(5): 1302-1312. |
| [9] | LIN Jiaxi, QIAN Qiuyan, ZENG Jianping, ZHANG Weidong. Surname Password Guessing Method Based on GPT-2 [J]. Journal of Frontiers of Computer Science and Technology, 2025, 19(4): 1087-1094. |
| [10] | CHANG Baofa, CHE Chao, LIANG Yan. Research on Recommendation Model Based on Multi-round Dialogue of Large Language Model [J]. Journal of Frontiers of Computer Science and Technology, 2025, 19(2): 385-395. |
| [11] | LI Boxin. Method of Retrieval-Augmented Large Language Models with Stable Outputs for Private Question-Answering Systems [J]. Journal of Frontiers of Computer Science and Technology, 2025, 19(1): 132-140. |
| [12] | WANG Yong, QIN Jiajun, HUANG Yourui, DENG Jiangzhou. Design of University Research Management Question Answering System Integrating Knowledge Graph and Large Language Models [J]. Journal of Frontiers of Computer Science and Technology, 2025, 19(1): 107-117. |
| [13] | XU Lei, HU Yahao, CHEN Man, CHEN Jun, PAN Zhisong. Hate Speech Detection Method Integrating Prefix Tuning and Prompt Learning [J]. Journal of Frontiers of Computer Science and Technology, 2025, 19(1): 97-106. |
| [14] | SANG Chenyang, MA Tinghuai, XIE Xintong, SUN Shengjie, HUANG Rui. Multi-stage Reasoning Method for Emotional Support Dialogue Generation Based on Large Language Models [J]. Journal of Frontiers of Computer Science and Technology, 2024, 18(11): 2925-2939. |
| [15] | ZENG Jun, WANG Ziwei, YU Yang, WEN Junhao, GAO Min. Word Embedding Methods in Natural Language Processing: a Review [J]. Journal of Frontiers of Computer Science and Technology, 2024, 18(1): 24-43. |
| Viewed | ||||||
|
Full text |
|
|||||
|
Abstract |
|
|||||
/D:/magtech/JO/Jwk3_kxyts/WEB-INF/classes/