Emerging role of artificial intelligence in gastroenterology and hepatology

Artificial intelligence (AI) has emerged as a transformative tool in the diagnosis and management of gastrointestinal (GI) and liver diseases. In clinical practice AI consists of overlapping technologies such as machine learning (ML), deep learning, natural language processing, computer vision, and generative AI. ML is a computer learning system that can provide insight into disease risk factors and phenotypes. Deep learning is an advanced and complex form of ML, structured with different levels of specific algorithms known as convolutional neural networks that can rapidly and accurately process unstructured, high-dimensional data, such as texts, images, and waveforms. Natural language processing is dedicated to facilitating interactions between computers and humans using natural language and helps to analyze, understand, and derive actionable information from unstructured healthcare data, including electronic health records, clinical notes, medical literature, and patient-generated content. Computer vision focuses on enabling computers to see and interpret images and videos and serves as an augmentation tool for endoscopists, improving accuracy and decreasing procedural time. Generative AI is capable of creating new forms of content by learning from a large body of data in the form of text, audio, images, or video and includes large language models. AI has been used in several GI diseases such as esophageal neoplasia, gastric cancer, <i>Helicobacter pylori</i> infection, gastritis, GI stromal tumors, colorectal polyps, inflammatory bowel disease, irritable bowel syndrome, GI bleeding, and pancreatobiliary diseases. The potential applications of AI in liver diseases encompass a variety of conditions such as liver masses, metabolic dysfunction-associated steatotic liver disease, viral hepatitis, cirrhosis, and liver transplantation. This review discussed the common terminologies and the current status of AI in gastroenterology and hepatology, exploring its applications and ethical issues.

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Publication Details

Journal
World Journal of Gastroenterology
Published
2025-10-21
DOI
https://doi.org/10.3748/wjg.v31.i39.111495
Citations
1
Primary Topic
Colorectal Cancer Screening and Detection
Type
article
Field-Weighted Citation Impact
1.05
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article

Emerging role of artificial intelligence in gastroenterology and hepatology

Utsav Shrestha
1 citations
World Journal of Gastroenterology
Colorectal Cancer Screening and Detection
1.05
article

Emerging role of artificial intelligence in gastroenterology and hepatology

Utsav Shrestha
article en
1 citations

Abstract

Artificial intelligence (AI) has emerged as a transformative tool in the diagnosis and management of gastrointestinal (GI) and liver diseases. In clinical practice AI consists of overlapping technologies such as machine learning (ML), deep learning, natural language processing, computer vision, and generative AI. ML is a computer learning system that can provide insight into disease risk factors and phenotypes. Deep learning is an advanced and complex form of ML, structured with different levels of specific algorithms known as convolutional neural networks that can rapidly and accurately process unstructured, high-dimensional data, such as texts, images, and waveforms. Natural language processing is dedicated to facilitating interactions between computers and humans using natural language and helps to analyze, understand, and derive actionable information from unstructured healthcare data, including electronic health records, clinical notes, medical literature, and patient-generated content. Computer vision focuses on enabling computers to see and interpret images and videos and serves as an augmentation tool for endoscopists, improving accuracy and decreasing procedural time. Generative AI is capable of creating new forms of content by learning from a large body of data in the form of text, audio, images, or video and includes large language models. AI has been used in several GI diseases such as esophageal neoplasia, gastric cancer, <i>Helicobacter pylori</i> infection, gastritis, GI stromal tumors, colorectal polyps, inflammatory bowel disease, irritable bowel syndrome, GI bleeding, and pancreatobiliary diseases. The potential applications of AI in liver diseases encompass a variety of conditions such as liver masses, metabolic dysfunction-associated steatotic liver disease, viral hepatitis, cirrhosis, and liver transplantation. This review discussed the common terminologies and the current status of AI in gastroenterology and hepatology, exploring its applications and ethical issues.

World Journal of GastroenterologyVol. 31(39)
Nepal Cancer Hospital and Research Center (NP)
Openalex Percentile: Top 17%
Colorectal Cancer Screening and Detection
1.05
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