A new AI model, LLaVA-Endo, dramatically improves diagnostic accuracy during gastrointestinal endoscopies by merging visual and language analysis.
Key Details
- 1LLaVA-Endo is developed by an international team including universities in China and the UAE.
- 2The model combines image recognition and natural language processing for GI endoscopy.
- 3It outperformed major AI systems, such as GPT-4V, Gemini, and MiniGPT-v2, on diagnostic tasks.
- 4LLaVA-Endo was validated through expert review and benchmark tests using thousands of annotated GI images.
- 5The study appears in Frontiers of Computer Science, with publication scheduled for April 2025.
Why It Matters
This innovation can standardize and improve the diagnostic accuracy of GI endoscopy, a challenging imaging domain with significant clinical impact. Its demonstrated superiority over big-tech AI models signals a leap in real-world applicability of radiology-oriented AI.

Source
EurekAlert
Related News

•EurekAlert
BraDiPho: New 3D AI Atlas Integrates Brain Dissections with MRI
Researchers have developed BraDiPho, a tool that merges ex-vivo photogrammetric brain dissection data with in-vivo MRI tractography using AI.

•EurekAlert
AI Maps Genetic Factors Shaping the Corpus Callosum via MRI Scans
USC researchers used AI to analyze MRI scans and uncover the genetic architecture of the brain's corpus callosum.

•EurekAlert
AI Accurately Detects Heart Disease via Smartwatch ECG in 600-Patient Study
An AI tool accurately detected structural heart disease from smartwatch single-lead ECGs in a 600-person prospective trial.