Machine learning algorithms based on proteomic data mining accurately predicting the recurrence of hepatitis B‐related hepatocellular carcinoma

• Published in: Journal of gastroenterology and hepatology Vol. 37; no. 11; pp. 2145 - 2153
• Main Authors: Feng, Gong, He, Na, Xia, Harry Hua‐Xiang, Mi, Man, Wang, Ke, Byrne, Christopher D, Targher, Giovanni, Yuan, Hai‐Yang, Zhang, Xin‐Lei, Zheng, Ming‐Hua, Ye, Feng
• Format: Journal Article
• Language: English
• Published: Richmond Wiley Subscription Services, Inc 01.11.2022
• Subjects: Algorithms; CPTAC database; Hepatitis; Hepatitis B; Hepatocellular carcinoma; Learning algorithms; Liver cancer; Machine learning; machine learning models; Prediction models; Proteins; Proteomics; recurrence of hepatocellular carcinoma; Survival; Survival analysis; Tumors

Background and Aim Over 10% of hepatocellular carcinoma (HCC) cases recur each year, even after surgical resection. Currently, there is a lack of knowledge about the causes of recurrence and the effective prevention. Prediction of HCC recurrence requires diagnostic markers endowed with high sensitiv...