Interpretable Machine Learning for Predicting Major Amputation Risk in Hospitalized Diabetic Foot Ulcer Patients
Summary: This study developed an interpretable machine learning model to predict major amputation risk among hospitalized patients with diabetic foot ulcers. The model offers good predictive accuracy while maintaining clinical interpretability, helping clinicians identify high-risk patients early for intensified multidisciplinary intervention.
Key Highlights:
- Focus on hospitalized DFU patients
- Interpretable ML model for clinical use
- Supports timely limb salvage decisions
- Addresses real-world amputation prevention needs
Keywords: DFU amputation risk, machine learning diabetic foot, limb salvage prediction