Machine learning for Healthcare

Foundations of ML in Healthcare

Learn the fundamentals of machine learning and its unique applications in clinical settings.

Clinical Risk Stratification Models

Build and evaluate models that identify high-risk patients for targeted interventions.

Natural Language Processing for Clinical Notes

Extract insights from unstructured clinical text using NLP techniques.

Cardiac Imaging and Diagnostic AI

Apply deep learning to interpret cardiac imaging data and automate diagnostic support.

Pathology Image Analysis and Tissue Classification

Develop models to classify tissue types and detect abnormalities in digital pathology images.

Deployment, Validation, and Clinical Impact

Learn to validate ML models in clinical settings and assess real-world healthcare impact.