GastroAGI Logo
OverviewBlogsAbout
Trending TopicsDaily BriefConference

Trending Topics in Gastroenterology

Explore current gastroenterology questions, clinical answers, and emerging research by topic.

31

GEMA-AI: Gender-Equity Model for Liver Transplant Waiting List Prioritization

GEMA-AI, or the Gender-Equity Model for Liver Transplant Waiting List Prioritization, is an innovative artificial intelligence-based model designed to improve fairness and accuracy in liver transplant allocation, with...

32

AI-assisted versus conventional reading in pan-intestinal capsule endoscopy

The comparison between AI-assisted pan-intestinal capsule endoscopy (AI-PCE) and conventional reading of pan-intestinal capsule endoscopy (CR-PCE) highlights significant advancements in the diagnostic capabilities of AI technology in the...

33

Machine learning in GI Endoscopy

Machine learning (ML) has revolutionized gastrointestinal (GI) endoscopy by improving diagnostic precision, reducing variability, and streamlining workflows. ML algorithms analyze endoscopic images or videos to detect patterns, identify...

34

Submucosal vessel detection during third-space endoscopy - Role of AI

The role of artificial intelligence (AI) in submucosal vessel detection during third-space endoscopy, such as endoscopic submucosal dissection (ESD) and peroral endoscopic myotomy (POEM), has been explored to...

35

CADe colonoscopy in colorectal cancer screening - ESGE Postional Statement

The ESGE (European Society of Gastrointestinal Endoscopy) Position Statement on computer-assisted detection (CADe) in colonoscopy for colorectal cancer (CRC) screening and post-polyp surveillance provides a cautious but favorable...

36

AI for submucosal vessel detection during third-space endoscopy

Submucosal vessel detection is critically important in third-space endoscopy because this advanced procedure involves creating a pathway within the layers of the gastrointestinal wall to treat conditions like...

37

Cancer Recurrence in Patients With CRC - Role of AI

The role of AI in detecting and analyzing cancer recurrence in patients with colorectal cancer (CRC) has been transformative, particularly with advancements like the DFCI-imaging-student model. Below is...

38

AI ML-based nomogram for mortality risk stratification in cirrhotic patients

The AI/ML-based nomogram developed in this study serves as a predictive tool for estimating in-hospital mortality risk among cirrhotic patients with sepsis. This retrospective single-center study analyzed data...

39

Deep learning : Predicting HCC surgery success with multimodal imaging

Deep learning is a subset of machine learning that uses artificial neural networks to model and analyze complex data patterns. It is particularly effective in tasks involving large...

40

Artificial intelligence-assisted colonoscopy improves adenoma detection rates

Yes, artificial intelligence (AI)-assisted colonoscopy has been shown to improve adenoma detection rates (ADR). Adenoma detection is a critical measure in colonoscopy, as higher ADRs are directly linked...

Previous
12345
Next
GastroAGI Logo

We are pioneers in clinical intelligence, dedicated to helping gastroenterologists harness the power of artificial intelligence to drive precision, efficiency, and patient growth.

For You

For StudentsFor CliniciansFor ResearchersFor Patients

Core Tools

MELD-Na ScoreChild-PughFIB-4 IndexGlasgow-BlatchfordBISAP Score

Explore

OverviewAboutCalculators
Trending Topics
Conference Briefings
Blog Insights
©GastroAGI 2026
Privacy PolicyTerms of UseMedical Disclaimer