Systematic Review of Machine Learning Models in Predicting the Risk of Bleed/Grade of Esophageal Varices in Patients with Liver Cirrhosis: A Comprehensive Methodological Analysis

• Main Authors: Malik, Sheza, Tenorio, Bettina Gabrielle, Moond, Vishali, Dahiya, Dushyant Singh, Vora, Ravi, Dbouk, Nader
• Format: text
• Published: Archīum Ateneo 2024
• Subjects: bleeding; esophageal varices; liver cirrhosis; machine learning; systematic review; variceal grade; Analytical, Diagnostic and Therapeutic Techniques and Equipment; Diseases; Gastroenterology; Hepatology; Medicine and Health Sciences
• Online Access: https://archium.ateneo.edu/asmph-pubs/262; https://doi.org/10.1111/jgh.16645
• Institution: Ateneo De Manila University

Esophageal varices (EV) in liver cirrhosis carry high mortality risks. Traditional endoscopy, which is costly and subjective, prompts a shift towards machine learning (ML). This review critically evaluates ML applications in predicting bleeding risks and grading EV in patients with liver cirrhosis....