The role of artificial intelligence in gastroenterology: Current perspectives and future directions-narrative review

Document Type

Article

Department

Pulmonary and Critical Care

Abstract

Background and objective: Artificial intelligence (AI) has revolutionized the field of gastroenterology, leading to significant improvements in the diagnosis, management, and prognosis of several gastrointestinal (GI) disorders. With this context in mind, this brief review examines a wide range of subjects, including the history of AI in medicine and the state of AI in gastroenterology today, with a particular emphasis on its application in radiographic diagnosis, endoscopic procedures, disease detection, and clinical decision-making.
Methods: A narrative review of the literature was conducted, encompassing studies published in English across major databases. The review covers historical developments of AI in medicine, contemporary AI applications in gastroenterology, and emerging trends.
Key content and findings: AI techniques, including machine learning and deep learning, have demonstrated high accuracy in detecting GI pathologies such as polyps, neoplasms, inflammatory bowel disease, and other conditions. AI applications in endoscopy, video capsule endoscopy, and colonoscopy enable rapid analysis of large datasets, aiding early diagnosis and clinical decision-making. Challenges identified include data quality, model interpretability, ethical concerns, and liability associated with AI-assisted clinical decisions. Despite these challenges, AI continues to enhance gastroenterology practice and shows promise for broader clinical adoption.
Conclusions: AI has significant potential to improve patient care in gastroenterology. Future advancements will require collaboration among AI developers, clinicians, and patients to address implementation barriers, optimize clinical utility, and inform policy and research directions.

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AKU Student

no

Publication (Name of Journal)

Translational Gastroenterology and Hepatology

DOI

10.21037/tgh-25-10

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