
A new AI tool, BIOPREVENT, predicts serious post-transplant complications months before symptoms appear using blood biomarkers and clinical data.
Key Details
- 1BIOPREVENT was developed by MUSC Hollings Cancer Center and validated with data from 1,310 transplant recipients.
- 2The tool outperformed standard clinical models in predicting chronic graft-versus-host disease (GVHD) and transplant-related death.
- 3BIOPREVENT uses seven immune protein biomarkers and nine clinical factors to assess risk.
- 4Predictions were validated in an independent patient cohort, showing reliable risk stratification up to 18 months post-transplant.
- 5A free, web-based application is available for clinicians to use the tool for research and risk assessment.
Why It Matters

Source
EurekAlert
Related News

AI and Ground-Penetrating Radar Innovate Detection of Hidden Steel Damage
University of Houston researchers developed an AI and radar-based method to detect hidden damage in cold-formed steel used in building structures.

NIH-Funded 'Merlin' Foundation Model Outperforms Specialists in CT AI Tasks
Stanford researchers unveil Merlin, a foundation AI model that outshines specialist models in analyzing 3D CT scans for diagnostics and disease prediction.

AI-powered Liquid Biopsy Detects Early Liver Fibrosis and Chronic Disease
AI-based cfDNA fragmentome liquid biopsy can detect early liver fibrosis, cirrhosis, and indicate broader chronic disease signals.