Exploring the benefits and challenges of AI-driven large language models in gastroenterology: Think out of the box

dc.contributor.authorKrál, Jancs
dc.contributor.authorHradiš, Michalcs
dc.contributor.authorBužga, Marekcs
dc.contributor.authorKunovský, Lumírcs
dc.coverage.issue4cs
dc.coverage.volume168cs
dc.date.issued2024-12-01cs
dc.description.abstractArtificial 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.en
dc.description.abstractArtificial 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.en
dc.formattextcs
dc.format.extent277-283cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationBIOMEDICAL PAPERS-OLOMOUC. 2024, vol. 168, issue 4, p. 277-283.en
dc.identifier.doi10.5507/bp.2024.027cs
dc.identifier.issn1213-8118cs
dc.identifier.orcid0000-0002-6364-129Xcs
dc.identifier.other197613cs
dc.identifier.researcheridG-9365-2016cs
dc.identifier.scopus23135162300cs
dc.identifier.urihttp://hdl.handle.net/11012/251910
dc.language.isoencs
dc.publisherPALACKY UNIV, MEDICAL FACcs
dc.relation.ispartofBIOMEDICAL PAPERS-OLOMOUCcs
dc.relation.urihttps://biomed.papers.upol.cz/pdfs/bio/2024/04/01.pdfcs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/1213-8118/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectartificial intelligenceen
dc.subjectlarge language modelen
dc.subjectgastroenterologyen
dc.subjectartificial intelligence
dc.subjectlarge language model
dc.subjectgastroenterology
dc.titleExploring the benefits and challenges of AI-driven large language models in gastroenterology: Think out of the boxen
dc.title.alternativeExploring the benefits and challenges of AI-driven large language models in gastroenterology: Think out of the boxen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-197613en
sync.item.dbtypeVAVen
sync.item.insts2025.10.14 14:13:22en
sync.item.modts2025.10.14 10:53:29en
thesis.grantorVysoké učení technické v Brně. . Vysoká škola báňská - Technická univerzita Ostravacs
thesis.grantorVysoké učení technické v Brně. . Univerzita Palackého v Olomoucics
thesis.grantorVysoké učení technické v Brně. . Univerzita Karlova v Prazecs
thesis.grantorVysoké učení technické v Brně. Fakulta informačních technologií. Ústav počítačové grafiky a multimédiícs
thesis.grantorVysoké učení technické v Brně. . Lékařská fakultacs
thesis.grantorVysoké učení technické v Brně. . MAIA LABS s.r.o.cs

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
BiomedPap_bio2024040001.pdf
Size:
892.94 KB
Format:
Adobe Portable Document Format
Description:
file BiomedPap_bio2024040001.pdf