Publications by authors named "Tevin Kim"
Article Synopsis
- Data-driven clinical prediction algorithms help clinicians, and understanding the factors that affect their performance and fairness is crucial for equitable healthcare.
- This study focused on creating a prediction algorithm for estimating glomerular filtration rate (GFR) using electronic health records (EHR) and compared three approaches: CKD-EPI equations, epidemiological models, and EHR-based models with various machine learning techniques.
- The findings revealed that while using more complex models and relevant clinical features reduced overall estimation error, the performance gap between African American and non-African American patients persisted, highlighting the need for better identification of objective patient characteristics to enhance algorithm fairness and effectiveness.
