Learning to Diagnose Privately: DP-Powered LLMs for Radiology Report Classification

1. 1Utilize Differential Privacy (DP) to protect sensitive patient information in radiology reports
2. 2Fine-tune LLMs on radiology report datasets to improve multi-abnormality classification accuracy
3. 3Evaluate the performance of DP-Powered LLMs using metrics such as accuracy, F1-score, and area under the ROC curve
4. 4Deploy DP-Powered LLMs in clinical settings to support disease diagnosis, abnormality classification, and clinical decision-making

Data scientists and AI engineers on healthcare teams benefit from this research as it enables private and accurate diagnosis of radiology reports, which can improve clinical workflow automation and biomedical research

💡 Differential Privacy (DP) can be used to protect sensitive patient information in radiology reports while maintaining accurate diagnosis

💡 DP-Powered LLMs enable private diagnosis of radiology reports #AIinHealthcare