An imaging-based machine learning model outperforms clinical risk scores for prognosis of cirrhotic variceal bleeding.

Yin GaoQian YuXiaohuan LiCong XiaJiaying ZhouTianyi XiaBen ZhaoYue QiuJun-Hao ZhaYuancheng WangTianyu TangYan LvJing YeChuanjun XuSheng-Hong Ju

Published in: European radiology (2023)

• The Liver-Spleen machine learning model (LS model) showed good performance in assessing the clinical composite endpoint of cirrhotic patients with AVB (AUC ≥ 0.782, sensitivity ≥ 80%). • The LS model outperformed the clinical scores (AUC ≤ 0.730, sensitivity ≤ 70%) in both internal and external test cohorts.

Keyphrases

machine learning
high resolution
artificial intelligence
big data
deep learning
photodynamic therapy