Department of Clinical Laboratory Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Department of Gastroenterology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
J Gastroenterol Hepatol. 2021 Mar;36(3):551-560. doi: 10.1111/jgh.15413.
Despite recent improvements in therapeutic interventions, hepatocellular carcinoma is still associated with a poor prognosis in patients with an advanced disease at diagnosis. Recently, significant progress has been made in image recognition through advances in the field of artificial intelligence (AI) (or machine learning), especially deep learning. AI is a multidisciplinary field that draws on the fields of computer science and mathematics for developing and implementing computer algorithms capable of maximizing the predictive accuracy from static or dynamic data sources using analytic or probabilistic models. Because of the multifactorial and complex nature of liver diseases, the machine learning approach to integrate multiple factors would appear to be an advantageous approach to improve the likelihood of making a precise diagnosis and predicting the response of treatment and prognosis of liver diseases. In this review, we attempted to summarize the potential use of AI in the diagnosis and management of liver diseases, especially hepatocellular carcinoma.
尽管治疗干预措施最近有所改进，但在诊断时疾病已处于晚期的患者中，肝细胞癌仍然预后不良。最近，人工智能（AI）（或机器学习）领域的进步使得图像识别取得了重大进展。AI 是一个多学科领域，它借鉴了计算机科学和数学领域的知识，用于开发和实施计算机算法，这些算法能够使用分析或概率模型从静态或动态数据源中最大化预测准确性。由于肝脏疾病的多因素和复杂性，机器学习方法集成多个因素似乎是一种有利的方法，可以提高精确诊断的可能性，并预测肝脏疾病的治疗反应和预后。在这篇综述中，我们试图总结 AI 在肝脏疾病，特别是肝细胞癌的诊断和管理中的潜在应用。
