AI Predicts Bedsore Risk in Hospital Patients: USC Study
AI Model Improves Early Detection of Hospital-Acquired Pressure Injuries
A collaborative study by USC, Johns Hopkins, and University Hospitals developed an AI model that significantly outperforms traditional tools in predicting hospital-acquired pressure injuries. Bayesian Health, led by Dr. Suchi Saria, contributed to the work, showcasing how its platform improves early detection, reduces nursing burden, and advances health equity through unbiased, data-driven risk assessment.
