Ability of Deep Learning to Predict Surgical Recommendations for Distal Radial Fractures: A Feasibility Study

This study investigates the feasibility of using artificial intelligence to predict whether a fellowship-trained hand surgeon would recommend operative or nonoperative management for distal radial fractures based on pre-reduction radiographs and clinical data. The developed model achieved high accuracy and sensitivity, indicating its potential utility in clinical decision-making. Future research will aim to validate the model externally and enhance its performance by incorporating more imaging features.