Predictive modeling for healthcare diagnostics

Thesis Abstract

Predictive modeling has shown great potential in improving healthcare diagnostics by enabling early detection of diseases and personalized treatment recommendations. This project aims to develop and evaluate predictive models for healthcare diagnostics, focusing on leveraging machine learning algorithms and clinical data to predict disease outcomes and support medical decision-making. The study will involve data collection, feature engineering, model training, and performance evaluation using real-world healthcare datasets. The findings will contribute to the development of predictive tools for enhancing diagnostic accuracy and patient care.