AI Model Enhances Prediction of Infection Risks from Oral Mucositis in Stem Cell Transplant Patients
Researchers developed an explainable AI tool that accurately predicts infection risks related to oral mucositis in hematopoietic stem cell transplant patients.
Key Details
- 1Patients with oral mucositis after HSCT are almost 4x more likely to develop serious infections.
- 2A new AI-driven nomogram using demographic and clinical features shows superior predictive accuracy versus traditional models.
- 3Explainable AI provided clinicians with rationale for predictions, enabling targeted preventive care.
- 4Meta-analysis identified high-risk groups and specific risk factors such as chemotherapy types, age, and kidney issues.
- 5Researchers are working towards broad clinical adoption, including validation for other adverse events in cancer therapy.
- 6Findings were recently published in the journal Cancers and presented at MASCC 2025.
Why It Matters

Source
EurekAlert
Related News

Researchers Develop All-Optical Synapse for Neuromorphic Imaging Systems
A new artificial synapse, controlled entirely by light, enables in-sensor neuromorphic processing for more efficient and noise-resistant imaging systems.

Mayo Clinic Showcases Imaging AI and Early Cancer Detection Advances at ASCO 2026
Mayo Clinic researchers will present over 30 studies at ASCO 2026, highlighting new advances in imaging AI, data science, and early cancer detection.

AI-Simulation Approach Achieves 90% Faster Brain MRI with Minimal Data
A simulation-based AI method can reconstruct brain MRI scans with only 10% of the usual data, greatly reducing scan times.