Exploring the benefits and challenges of AI-driven large language models in gastroenterology: Think out of the box
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Date
2024-12-01
Authors
Král, Jan
Hradiš, Michal
Bužga, Marek
Kunovský, Lumír
ORCID
0000-0002-6364-129XAdvisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
PALACKY UNIV, MEDICAL FAC
Altmetrics
Abstract
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 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.
Description
Citation
Biomedical Papers. 2024, vol. 168, issue 4, p. 277-283.
https://biomed.papers.upol.cz/pdfs/bio/2024/04/01.pdf
https://biomed.papers.upol.cz/pdfs/bio/2024/04/01.pdf
Document type
Peer-reviewed
Document version
Published version
Date of access to the full text
Language of document
en