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Related Experiment Video

Updated: Apr 6, 2026

Author Spotlight: Generation of and Comparison Between Patient-Derived Gastric Organoids from Different Regions of the Stomach

Author Spotlight: Generation of and Comparison Between Patient-Derived Gastric Organoids from Different Regions of the Stomach

Published on: January 26, 2024

Artificial Intelligence Tools for Gastrointestinal Research: A Practical Guide.

Christina S Gainey¹, Hersh Shroff¹, Oren K Fix¹

¹Division of Gastroenterology and Hepatology, University of North Carolina, Chapel Hill, North Carolina.

Clinical Gastroenterology and Hepatology : the Official Clinical Practice Journal of the American Gastroenterological Association

|April 5, 2026

Summary

This summary is machine-generated.

Artificial intelligence (AI) tools can aid manuscript writing for gastroenterology (GI) researchers. Responsible use with human verification is key to accelerating the process and ensuring accuracy.

Keywords:

Artificial Intelligence Gastroenterology Large Language Models Manuscript Writing Scientific Publishing

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Area of Science:

Biomedical Research
Artificial Intelligence in Science
Gastroenterology

Background:

Growing adoption of AI tools, including large language models (LLMs), in biomedical research.
Limited practical guidance for integrating AI into manuscript writing workflows.
Need for structured approaches for GI researchers and clinicians.

Purpose of the Study:

Provide a step-by-step guide for responsible AI use in GI manuscript preparation.
Evaluate AI tools for literature searching, data analysis, figure generation, and drafting.
Offer a risk-stratified framework for AI integration.

Main Methods:

Literature review, expert recommendations, and author evaluation of AI tools.
Selection based on relevance to GI manuscript workflow, availability, and maintenance.
Assessment across four domains: literature search, data analysis, figure generation, manuscript drafting/editing.
GI-specific examples and head-to-head comparisons.
Risk assessment for fabrication, bias, and misuse.

Main Results:

AI tools effectively synthesize literature/data, generate statistical code for visualizations, draft tables/figures, and refine academic writing.
Tool maturity varies; general LLMs show high reference fabrication rates.
AI-generated images may lack necessary precision.
Independent verification of all AI outputs is crucial.

Conclusions:

AI tools can accelerate GI manuscript writing with proper safeguards.
A risk-stratified framework is proposed, emphasizing essential human verification.
Transparent disclosure of AI use is recommended for all submissions.