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Application of Machine Learning Based on Structured Medical Data in Gastroenterology

The era of big data has led to the necessity of artificial intelligence models to effectively handle the vast amount of clinical data available. These data have become indispensable resources for machine learning. Among the artificial intelligence models, deep learning has gained prominence and is w...

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Detalles Bibliográficos
Autores principales: Kim, Hye-Jin, Gong, Eun-Jeong, Bang, Chang-Seok
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10669027/
https://www.ncbi.nlm.nih.gov/pubmed/37999153
http://dx.doi.org/10.3390/biomimetics8070512
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author Kim, Hye-Jin
Gong, Eun-Jeong
Bang, Chang-Seok
author_facet Kim, Hye-Jin
Gong, Eun-Jeong
Bang, Chang-Seok
author_sort Kim, Hye-Jin
collection PubMed
description The era of big data has led to the necessity of artificial intelligence models to effectively handle the vast amount of clinical data available. These data have become indispensable resources for machine learning. Among the artificial intelligence models, deep learning has gained prominence and is widely used for analyzing unstructured data. Despite the recent advancement in deep learning, traditional machine learning models still hold significant potential for enhancing healthcare efficiency, especially for structured data. In the field of medicine, machine learning models have been applied to predict diagnoses and prognoses for various diseases. However, the adoption of machine learning models in gastroenterology has been relatively limited compared to traditional statistical models or deep learning approaches. This narrative review provides an overview of the current status of machine learning adoption in gastroenterology and discusses future directions. Additionally, it briefly summarizes recent advances in large language models.
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spelling pubmed-106690272023-10-28 Application of Machine Learning Based on Structured Medical Data in Gastroenterology Kim, Hye-Jin Gong, Eun-Jeong Bang, Chang-Seok Biomimetics (Basel) Review The era of big data has led to the necessity of artificial intelligence models to effectively handle the vast amount of clinical data available. These data have become indispensable resources for machine learning. Among the artificial intelligence models, deep learning has gained prominence and is widely used for analyzing unstructured data. Despite the recent advancement in deep learning, traditional machine learning models still hold significant potential for enhancing healthcare efficiency, especially for structured data. In the field of medicine, machine learning models have been applied to predict diagnoses and prognoses for various diseases. However, the adoption of machine learning models in gastroenterology has been relatively limited compared to traditional statistical models or deep learning approaches. This narrative review provides an overview of the current status of machine learning adoption in gastroenterology and discusses future directions. Additionally, it briefly summarizes recent advances in large language models. MDPI 2023-10-28 /pmc/articles/PMC10669027/ /pubmed/37999153 http://dx.doi.org/10.3390/biomimetics8070512 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Kim, Hye-Jin
Gong, Eun-Jeong
Bang, Chang-Seok
Application of Machine Learning Based on Structured Medical Data in Gastroenterology
title Application of Machine Learning Based on Structured Medical Data in Gastroenterology
title_full Application of Machine Learning Based on Structured Medical Data in Gastroenterology
title_fullStr Application of Machine Learning Based on Structured Medical Data in Gastroenterology
title_full_unstemmed Application of Machine Learning Based on Structured Medical Data in Gastroenterology
title_short Application of Machine Learning Based on Structured Medical Data in Gastroenterology
title_sort application of machine learning based on structured medical data in gastroenterology
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10669027/
https://www.ncbi.nlm.nih.gov/pubmed/37999153
http://dx.doi.org/10.3390/biomimetics8070512
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