Translational artificial intelligence in gastrointestinal and hepatic disorders: Advancing intelligent clinical decision-making for diagnosis, treatment, and prognosis
Year: 2025
Type: article
Abstract: Gastrointestinal and hepatic disorders exhibit significant heterogeneity, characterized by complex and diverse clinical phenotypes. Most lesions present without typical symptoms in their early stages, which poses substantial challenges for early clinical identification and intervention. As an interdisciplinary field at the forefront of technology, artificial intelligence (AI) integrates theoretical innovation, algorithm development, and engineering applications, triggering paradigm shifts within the medical field. Current research trends indicate that AI technology is progressively permeating the entire diagnostic and therapeutic process for gastrointestinal and hepatic disorders, facilitating intelligent transformations in precise lesion detection, optimization of treatment decisions, and prognosis evaluation through the integration of different modal data, construction of intelligent algorithms, and establishment of clinical verification systems. This article systematically reviews the latest advancements in AI technology concerning the diagnosis and treatment of gastrointestinal diseases (such as inflammatory bowel disease and digestive system tumors) and hepatic diseases (including hepato-cirrhosis and liver cancer), emphasizing its application value and transformative potential in critical areas such as imaging omics analysis, endoscopic intelligent identification, and personalized treatment prediction.
Authors: Shu-Qi Ren, Jin-Man Chen, Chuang Cai
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4414344904