Content for the AI In Healthcare Specialization section. C2 Clinical Data ↳ [ToC] Course 2 ↳ [Summary] Module 1: Asking Answering Questions via Clinical DataMining ↳ [Summary] Module2: Data Available From Healthcare Systems ↳ [Summary] Module3: Representing Time Timing Events For Clinical Data Mining ↳ [Summary] Module4 : Creating Analysis Ready Dataset from Patient Timelines ↳ Clinical Text Feature Extraction Using Dictionary-Based Filtering ↳ Clinical Text Mining Pipeline (Steps 1–5) ↳ Ethics in AI for Healthcare ↳ Missing Data Scenarios in Healthcare Modeling ↳ OMOP vs. RLHF ↳ Rule-Based Electronic Phenotyping Example: Type 2 Diabetes C3 ML Healthcare ↳ [ToC] Course 3 ↳ [Summary] Module 3: Concepts and Principles of ML in Healthcare ↳ [Summary] Module 4: Evaluation and Metrics for ML in Healthcare ↳ [Summary] Module 5: Strategies and Challenges in ML for Healthcare ↳ [Summary] Module 6: Best Practices, Terms, and Launching Your ML Journey ↳ [Summary] Module 7: Foundation Models ↳ Case Study: The Hidden Danger of Correlation in Healthcare AI ↳ Categories of Machine Learning Applications in Healthcare ↳ Data Quality, Labeling, and Weak Supervision in Clinical ML ↳ Diagnostic Metrics, Anchoring Perspectives, and Curve Interpretations ↳ Foundation Models for Healthcare ↳ Healthcare Use Cases for Non-textual Unstructured Data ↳ Healthcare Use Cases for Text Data ↳ How Foundation Models Work ↳ Output-Action Pairing (OAP) Framework in Healthcare ↳ Tradeoffs in Machine Learning: Precision vs. Recall in Healthcare C4 AI Evaluations ↳ [ToC] Course 4 C5 Capstone Projects
