Using AI to predict outcomes in diverticulitis

Prediction of outcomes in diverticulitis using a deep-learning framework

['FUNDING_CAREER'] · MASSACHUSETTS GENERAL HOSPITAL · NIH-11010795

This study is looking at how smart computer technology can help doctors understand the risks of complications and recurrences in patients with diverticulitis by analyzing medical records and CT scans, which could lead to better treatment choices and improved care for you.

Quick facts

Phase['FUNDING_CAREER']
Study typeNih_funding
SexAll
SponsorMASSACHUSETTS GENERAL HOSPITAL (nih funded)
Locations1 site (BOSTON, UNITED STATES)
Trial IDNIH-11010795 on ClinicalTrials.gov

What this research studies

This research investigates how artificial intelligence can analyze clinical data and imaging to predict the likelihood of complications and recurrences in patients with diverticulitis. By utilizing natural language processing for clinical notes and deep learning for abdominal CT scans, the study aims to identify patients at higher risk for adverse outcomes. This personalized approach could help guide treatment decisions, potentially improving patient management and outcomes.

Who could benefit from this research

Good fit: Ideal candidates for this research are individuals experiencing their first episode of diverticulitis, particularly those at risk for complications.

Not a fit: Patients with a history of recurrent diverticulitis or those who have already undergone surgical intervention may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could lead to better prediction of complications in diverticulitis, allowing for more tailored and effective treatment plans.

How similar studies have performed: Other research has shown promise in using AI for predicting medical outcomes, suggesting that this approach could be effective in the context of diverticulitis.

Where this research is happening

BOSTON, UNITED STATES

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.

View on NIH RePORTER →

Last reviewed 2026-05-15 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.