Artificial intelligence in the diagnosis and management of hepatocellular carcinoma

• Published in: Journal of gastroenterology and hepatology Vol. 36; no. 3; pp. 551 - 560
• Main Authors: Sato, Masaya, Tateishi, Ryosuke, Yatomi, Yutaka, Koike, Kazuhiko
• Format: Journal Article
• Language: English
• Published: Australia Wiley Subscription Services, Inc 01.03.2021
• Subjects: Artificial intelligence; Deep learning; Diagnosis; Hepatocellular carcinoma; Learning algorithms; Liver cancer; Liver diseases; Machine learning; Mathematical models; predictive model; Prognosis; Therapeutic applications; deep learning; predictive model; machine learning; artificial intelligence; hepatocellular carcinoma
• ISSN: 0815-9319; 1440-1746; 1440-1746
• 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.