人工智能（AI）在非酒精性脂肪肝（NAFLD）研究中的应用：系统综述

摘要(中文译文)

非酒精性脂肪性肝病（NAFLD）是全球慢性肝病最重要的病因之一，研究发现心血管和肾脏风险及疾病在NAFLD成人中同样高度流行。尽管医学科学已非常发达，NAFLD的诊断和治疗仍面临诸多挑战，效率、准确性和个体化是亟待解决的主要目标。NAFLD严重程度的评估涉及多种临床参数，如何优化无创评估方法是该领域需要讨论的必要议题。人工智能（AI）在医疗保健应用日益广泛，也为更好地分析慢性肝病（包括NAFLD）带来了许多新见解。本文综述了近期发表的AI在NAFLD领域的相关研究，总结了基于电子健康记录和实验室检查、超声和放射影像以及肝脏组织病理学数据的诊断模型，描述了治疗模型在个性化生活方式指导和NAFLD药物研发中的应用。此外，我们还分析了当前AI模型在NAFLD进展评估中区分健康与NAFLD/NASH、纤维化与非纤维化的应用。我们希望为未来研究提供替代方向。

Abstract

Non-alcoholic fatty liver disease (NAFLD) is one of the most important causes of chronic liver disease in the world, it has been found that cardiovascular and renal risks and diseases are also highly prevalent in adults with NAFLD. Diagnosis and treatment of NAFLD face many challenges, although the medical science has been very developed. Efficiency, accuracy and individualization are the main goals to be solved. Evaluation of the severity of NAFLD involves a variety of clinical parameters, how to optimize non-invasive evaluation methods is a necessary issue that needs to be discussed in this field. Artificial intelligence (AI) has become increasingly widespread in healthcare applications, and it has been also brought many new insights into better analyzing chronic liver disease, including NAFLD. This paper reviewed AI related researches in NAFLD field published recently, summarized diagnostic models based on electronic health record and lab test, ultrasound and radio imaging, and liver histopathological data, described the application of therapeutic models in personalized lifestyle guidance and the development of drugs for NAFLD. In addition, we also analyzed present AI models in distinguishing healthy VS NAFLD/NASH, and fibrosis VS non-fibrosis in the evaluation of NAFLD progression. We hope to provide alternative directions for the future research.

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