Integrating Causality, Temporal Learning, and Fairness for Hospital Readmission Prediction in Diabetic Patients

This coursework presentation explores predictive modeling for hospital readmission in diabetic patients, emphasizing causality, temporal learning, and fairness. Beginning with motivation and problem statement, it addresses the ethical and cost challenges in traditional models. It introduces an objective to integrate causal inference and LSTM strategies, ensuring fairness and optimization in the prediction process. The design incorporates clear themes and diagram placeholders for an engaging...