At the ECCO 2025 Congress, researchers presented a study showing that machine learning can identify gut microbial biomarkers that differentiate IBD patients—particularly those with Crohn’s disease—from healthy individuals. The study analyzed stool samples from over 3,700 participants, finding that supervised machine learning had the highest diagnostic accuracy (AUC 0.971).
Trending
- Multitarget Stool DNA Versus Fecal Immunochemical Testing: A National Assessment of Follow-Up Colonoscopy by Race and Ethnicity (National Comprehensive Cancer Network)
- Physician Fee Schedule 2027: What physicians need to know now (Medical Economics)
- Agenus Announces Oversubscribed Private Placement of Up to $340 Million to Advance Registrational ROBBIN Trial of Neoadjuvant BOT+BAL in MSS Colon Cancer (Business Wire)
- What Happens to Independent Medicine When Private Equity Shows Up With a Checkbook (MedCity News)
- AGA launches AI-powered virtual assistant for gastroenterology and hepatology care (News Medical)
- AMSURG Acquires 5 Endoscopy Centers in North Carolina (ASC News)
- Hawaii mandates free follow-up colonoscopies, wipes $91M in medical debt (Becker’s Healthcare)
- Endo Tools Therapeutics Secures $23 million in Series C Financing to Advance The endomina® technology and Commercialization of New endomina EZFuse System (Endo Tools Therapeutics)
