Artificial intelligence in the diagnosis and management of hepatocellular carcinoma

被引：19

作者：

Sato, Masaya ^{[1
,2
]}

Tateishi, Ryosuke ^{[2
]}

Yatomi, Yutaka ^{[1
]}

Koike, Kazuhiko ^{[2
]}

机构：

[1] Univ Tokyo, Grad Sch Med, Dept Clin Lab Med, Tokyo, Japan

[2] Univ Tokyo, Grad Sch Med, Dept Gastroenterol, Tokyo, Japan

来源：

JOURNAL OF GASTROENTEROLOGY AND HEPATOLOGY | 2021年 / 36卷 / 03期

关键词：

artificial intelligence; deep learning; hepatocellular carcinoma; machine learning; predictive model; RADIOMICS; SURVIVAL; CANCER; MODEL;

D O I：

10.1111/jgh.15413

中图分类号：

R57 [消化系及腹部疾病];

学科分类号：

摘要：

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.

引用

页码：551 / 560

页数：10

共 54 条

[1] Predicting Treatment Response to Intra-arterial Therapies for Hepatocellular Carcinoma with the Use of Supervised Machine Learning -An Artificial Intelligence Concept [J].