Artificial Intelligence (AI) has evolved significantly over the past decades, from its early concepts in the 1950s to the present era of deep learning and natural language processing. Advanced large language models (LLMs), such as Chatbot Generative Pre-Trained Transformer (ChatGPT) is trained to generate human-like text responses. This technology has the potential to revolutionize various aspects of gastroenterology, including diagnosis, treatment, education, and decision-making support. The benefits of using LLMs in gastroenterology could include accelerating diagnosis and treatment, providing personalized care, enhancing education and training, assisting in decision-making, and improving communication with patients. However, drawbacks and challenges such as limited AI capability, training on possibly biased data, data errors, security and privacy concerns, and implementation costs must be addressed to ensure the responsible and effective use of this technology. The future of LLMs in gastroenterology relies on the ability to process and analyse large amounts of data, identify patterns, and summarize information and thus assist physicians in creating personalized treatment plans. As AI advances, LLMs will become more accurate and efficient, allowing for faster diagnosis and treatment of gastroenterological conditions. Ensuring effective collaboration between AI developers, healthcare professionals, and regulatory bodies is essential for the responsible and effective use of this technology. By finding the right balance between AI and human expertise and addressing the limitations and risks associated with its use, LLMs can play an increasingly significant role in gastroenterology, contributing to better patient care and supporting doctors in their work.

2nd Department of Internal Medicine Gastroenterology and Geriatrics University Hospital Olomouc and Faculty of Medicine and Dentistry Palacky University Olomouc Olomouc Czech Republic

Department of Gastroenterology and Digestive Endoscopy Masaryk Memorial Cancer Institute Brno Czech Republic

Department of Hepatogastroenterology Institute for Clinical and Experimental Medicine Prague Czech Republic

Department of Internal Medicine University Hospital Motol and 2nd Faculty of Medicine Charles University Prague Czech Republic

Department of Physiology and Pathophysiology Faculty of Medicine University of Ostrava Ostrava Czech Republic

Department of Surgery University Hospital Brno and Faculty of Medicine Masaryk University Brno Czech Republic

Faculty of Information Technology University of Technology Brno Czech Republic

Institute of Laboratory Medicine University Hospital Ostrava Ostrava Czech Republic

MAIA LABS s r o Brno Czech Republic

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Kaul V, Enslin S, Gross SA. History of artificial intelligence in medicine. Gastrointest Endosc 2020;92:807-12. doi: 10.1016/j.gie.2020.06.040 PubMed DOI

Toosi A, Bottino AG, Saboury B, Siegel E, Rahmim A. A Brief History of AI: How to Prevent Another Winter (A Critical Review). PET Clin 2021;16:449-69. doi: 10.1016/j.cpet.2021.07.001 PubMed DOI

Egger J, Gsaxner C, Pepe A, Pomykala KL, Jonske F, Kurz M, Li J, Kleesiek J. Medical deep learning-A systematic meta-review. Comput Methods Programs Biomed 2022;221:106874. doi: 10.1016/j.cmpb.2022.106874 PubMed DOI

Haug CJ, Drazen JM. Artificial Intelligence and Machine Learning in Clinical Medicine, 2023. N Engl J Med 2023;388(13):1201-8. doi: 10.1056/NEJMra2302038 PubMed DOI

Harrer S. Attention is not all you need: the complicated case of ethically using large language models in healthcare and medicine. Ebiomedicine 2023;90:104512. doi: 10.1016/j.ebiom.2023.104512 PubMed DOI

Esteva A, Robicquet A, Ramsundar B, Kuleshov V, DePristo M, Chou K, Cui C, Corrado G, Thrun S, Dean J. A guide to deep learning in healthcare. Nat Med 2019;25(1):24-9. doi: 10.1038/s41591-018-0316-z PubMed DOI

Brown T, Mann B, Ryder N, Subbiah M, Kaplan J, Dhariwal P, Neelakantan A, Shyam P, Sastry G, Askell A, Agarwal S, Herbert-Voss A, Krueger G, Henighan T, Child R, Ramesh A, Ziegler D, Wu J, Winter C, Amodei D. Language Models are Few-Shot Learners. Arxiv 2020. Available from: https://arxiv.org/abs/2005.14165

Naveed H, Khan AU, Qiu S, Saqib M, Anwar S, Usman U, Akhtar N, Barnes N, Mian A. A Comprehensive Overview of Large Language Models. Arxiv 2023. Available from: https://doi.org/10.48550/arXiv.2307.06435 DOI

Fedus W, B. Z., Shazeer N. Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity. Arxiv 2021. Available from: https://arxiv.org/abs/2101.03961

Cretu C. How Does ChatGPT Actually Work? An ML Engineer Explains. Arxiv 2023. Available from: https://www.scalablepath.com/data-science/chatgpt-architecture-explained

Josh A, Adler S, Agarwal S, Ahmad L, Akkaya I, Aleman FL. GPT-4 Technical Report. Arxiv 2023. Available from: https://arxiv.org/abs/2303.08774

Bubeck S, Chandrasekaran V, Eldan R, Gehrke J, Horvitz E, Kamar E, Lee P, Lee YT, Li Y, Lundberg S, Nori H, Palangi H, Ribeiro MT, Zhang Y. Sparks of Artificial General Intelligence: Early experiments with GPT-4. Arxiv 2023. Available from: https://doi.org/10.48550/arXiv.2303.12712 DOI

Alberts IL, Mercolli L, Pyka T, Prenosil G, Shi K, Rominger A, Afshar-Oromieh A. Large language models (LLM) and ChatGPT: what will the impact on nuclear medicine be? Eur J Nucl Med Mol Imaging 2023;50(6):1549-52. doi: 10.1007/s00259-023-06172-w PubMed DOI

Nori H, King N, Mayer McKinney S, Carignan D, Horvitz E. Capabilities of GPT-4 on Medical Challenge Problems. Arxiv 2023. Available from: https://doi.org:doi.org/10.48550/arXiv.2303.13375

OpenAI. Introducing ChatGPT. 2022 Available from: https://openai.com/index/chatgpt/

Sharma P, Parasa S. ChatGPT and large language models in gastroenterology. Nat Rev Gastroenterol Hepatol 2023;20(8):481-2. doi: 10.1038/s41575-023-00799-8 PubMed DOI

Sallam M. ChatGPT Utility in Healthcare Education, Research, and Practice: Systematic Review on the Promising Perspectives and Valid Concerns. Healthcare (Basel) 2023;11(6):887. doi: 10.3390/healthcare11060887 PubMed DOI

Norori N, Hu Q, Aellen FM, Faraci FD, Tzovara A. Addressing bias in big data and AI for health care: A call for open science. Patterns (N Y) 2021;2(10):100347. doi: 10.1016/j.patter.2021.100347 PubMed DOI

Shahab O, El Kurdi B, Shaukat A, Nadkarni G, Soroush A. Large language models: a primer and gastroenterology applications. Therap Adv Gastroenterol 2024;17:17562848241227031. doi: 10.1177/17562848241227031 PubMed DOI

Wang F, Preininger A. AI in Health: State of the Art, Challenges, and Future Directions. Yearb Med Inform 2019;28(1):16-26. doi: 10.1055/s-0039-1677908 PubMed DOI

Le Berre C, Sandborn WJ, Aridhi S, Devignes MD, Fournier L, Smaïl-Tabbone M, Danese S, Peyrin-Biroulet L. Application of Artificial Intelligence to Gastroenterology and Hepatology. Gastroenterology 2020;158(1):76-94.e2. doi: 10.1053/j.gastro.2019.08.058 PubMed DOI

Zhuang H, Zhang J, Liao F. A systematic review on application of deep learning in digestive system image processing. Vis Comput 2023;39(6):2207-22. doi: 10.1007/s00371-021-02322-z PubMed DOI

Li W, Zhang Y, Chen F. ChatGPT in Colorectal Surgery: A Promising Tool or a Passing Fad? Ann Biomed Eng 2023;51(9):1892-7. doi: 10.1007/s10439-023-03232-y PubMed DOI

Seong D, Choi YH, Shin SY, Yi BK. Deep learning approach to detection of colonoscopic information from unstructured reports. BMC Med Inform Decis Mak 2023;23(1):28. doi: 10.1186/s12911-023-02121-7 PubMed DOI

Barrett JS, Oskoui SE, Russell S, Borens A. Digital Research Environment(DRE)-enabled Artificial Intelligence (AI) to facilitate early stage drug development. Front Pharmacol 2023;14:1115356. doi: 10.3389/fphar.2023.1115356 PubMed DOI

Lahat A, Shachar E, Avidan B, Shatz Z, Glicksberg BS, Klang E. Evaluating the use of large language model in identifying top research questions in gastroenterology. Sci Rep 2023;13(1):4164. doi: 10.1038/s41598-023-31412-2 PubMed DOI

WHO. Growing use of AI for health presents governments, providers, and communities with opportunities and challenges. 2021 Available from: https://www.who.int/news/item/28-06-2021-who-issues-first-global-report-on-ai-in-health-and-six-guiding-principles-for-its-design-and-use

FDA. Using artificial intelligence and machine learning in the development of drugs and biological products. Discussion paper and request for feedback. 2023 Available from: https://www.fda.gov/media/167973/download

Lee TC, Staller K, Botoman V, Pathipati MP, Varma S, Kuo B. ChatGPT Answers Common Patient Questions About Colonoscopy. Gastroenterology 2023;165(2):509-511.e7. doi: 10.1053/j.gastro.2023.04.033 PubMed DOI

McDuff D, Schaekermann M. Towards Accurate Differential Diagnosis with Large Language Models. ArXiv 2023. Available from: Towards Accurate Differential Diagnosis with Large Language Models

Ali S. Where do we stand in AI for endoscopic image analysis? Deciphering gaps and future directions. NPJ Digit Med 202;5(1):184. doi: 10.1038/s41746-022-00733-3 PubMed DOI

De Angelis L, Baglivo F, Arzilli G, Privitera GP, Ferragina P, Tozzi AE, Rizzo C. ChatGPT and the rise of large language models: the new AI-driven infodemic threat in public health. Front Public Health 2023;11:1166120. doi: 10.3389/fpubh.2023.1166120 PubMed DOI

Murdoch B. Privacy and artificial intelligence: challenges for protecting health information in a new era. BMC Med Ethics 202;22(1):122. doi: 10.1186/s12910-021-00687-3 PubMed DOI

Meskó B, Topol EJ. The imperative for regulatory oversight of large language models (or generative AI) in healthcare. NPJ Digit Med 2023;6(1):120. doi: 10.1038/s41746-023-00873-0 PubMed DOI

Commission E. Ethics Guidelines for Trustworthy AI. 2021 Available from: https://ec.europa.eu/futurium/en/ai-alliance-consultation.1.html

Commission E. A European approach to artificial intelligence. 2023 Available from: https://digital-strategy.ec.europa.eu/en/policies/european-approach-artificial-intelligence

Jill M. Security, Privacy Risks of Artificial Intelligence in Healthcare. 2021 Available from: https://healthitsecurity.com/features/security-privacy-risks-of-artificial-intelligence-in-healthcare

Clusmann J, Kolbinger FR, Muti HS, Carrero ZI, Eckardt JN, Laleh NG, Löffler CML, Schwarzkopf SC, Unger M, Veldhuizen GP, Wagner SJ, Kather JN. The future landscape of large language models in medicine. Commun Med (Lond) 2023;3(1):141. doi: 10.1038/s43856-023-00370-1 PubMed DOI

Ascending the "Hill" of Artificial Intelligence in Upper Gastrointestinal Endoscopy