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Artificial Intelligence in NAFLD: Will Liver Biopsy Still Be Necessary in the Future?
As the advanced form of nonalcoholic fatty liver disease (NAFLD), nonalcoholic steatohepatitis (NASH) will significantly increase the risks of liver fibrosis, cirrhosis, and HCC. However, there is no non-invasive method to distinguish NASH from NAFLD so far. Additionally, liver biopsy remains the go...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9818843/ https://www.ncbi.nlm.nih.gov/pubmed/36611577 http://dx.doi.org/10.3390/healthcare11010117 |
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author | Zhang, Lei Mao, Yilei |
author_facet | Zhang, Lei Mao, Yilei |
author_sort | Zhang, Lei |
collection | PubMed |
description | As the advanced form of nonalcoholic fatty liver disease (NAFLD), nonalcoholic steatohepatitis (NASH) will significantly increase the risks of liver fibrosis, cirrhosis, and HCC. However, there is no non-invasive method to distinguish NASH from NAFLD so far. Additionally, liver biopsy remains the gold standard to diagnose NASH, which is not appropriate for routine screening. Recently, artificial intelligence (AI) is under rapid development in many aspects of medicine. Additionally, the application of AI in clinical information may have the potential to diagnose NASH non-invasively. This review summarizes the latest research using AI, specifically machine learning, to facilitate the diagnosis, prognosis, and monitoring of NAFLD. Additionally, according to our prior results, this work proposes future development in this area. |
format | Online Article Text |
id | pubmed-9818843 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98188432023-01-07 Artificial Intelligence in NAFLD: Will Liver Biopsy Still Be Necessary in the Future? Zhang, Lei Mao, Yilei Healthcare (Basel) Review As the advanced form of nonalcoholic fatty liver disease (NAFLD), nonalcoholic steatohepatitis (NASH) will significantly increase the risks of liver fibrosis, cirrhosis, and HCC. However, there is no non-invasive method to distinguish NASH from NAFLD so far. Additionally, liver biopsy remains the gold standard to diagnose NASH, which is not appropriate for routine screening. Recently, artificial intelligence (AI) is under rapid development in many aspects of medicine. Additionally, the application of AI in clinical information may have the potential to diagnose NASH non-invasively. This review summarizes the latest research using AI, specifically machine learning, to facilitate the diagnosis, prognosis, and monitoring of NAFLD. Additionally, according to our prior results, this work proposes future development in this area. MDPI 2022-12-30 /pmc/articles/PMC9818843/ /pubmed/36611577 http://dx.doi.org/10.3390/healthcare11010117 Text en © 2022 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 Zhang, Lei Mao, Yilei Artificial Intelligence in NAFLD: Will Liver Biopsy Still Be Necessary in the Future? |
title | Artificial Intelligence in NAFLD: Will Liver Biopsy Still Be Necessary in the Future? |
title_full | Artificial Intelligence in NAFLD: Will Liver Biopsy Still Be Necessary in the Future? |
title_fullStr | Artificial Intelligence in NAFLD: Will Liver Biopsy Still Be Necessary in the Future? |
title_full_unstemmed | Artificial Intelligence in NAFLD: Will Liver Biopsy Still Be Necessary in the Future? |
title_short | Artificial Intelligence in NAFLD: Will Liver Biopsy Still Be Necessary in the Future? |
title_sort | artificial intelligence in nafld: will liver biopsy still be necessary in the future? |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9818843/ https://www.ncbi.nlm.nih.gov/pubmed/36611577 http://dx.doi.org/10.3390/healthcare11010117 |
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