Zhang Lei, Mao Yilei
Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
Healthcare (Basel). 2022 Dec 30;11(1):117. doi: 10.3390/healthcare11010117.
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.
作为非酒精性脂肪性肝病（NAFLD）的晚期形式，非酒精性脂肪性肝炎（NASH）会显著增加肝纤维化、肝硬化和肝癌（HCC）的风险。然而，目前尚无区分NASH与NAFLD的非侵入性方法。此外，肝活检仍是诊断NASH的金标准，但不适用于常规筛查。近年来，人工智能（AI）在医学的许多领域都在迅速发展。此外，AI在临床信息中的应用可能具有非侵入性诊断NASH的潜力。本综述总结了利用AI，特别是机器学习，来促进NAFLD的诊断、预后和监测的最新研究。此外，根据我们之前的研究结果，本文提出了该领域未来的发展方向。
