| 1 |
Introduction |
Lecture 1 |
| 2 |
Classifiers in Health Care |
Lecture 2 |
| 3 |
Data Transformations and Decision Trees |
Lecture 3 |
| 4 |
Random Forests and Wearables applications |
Lecture 4 |
| 5 |
Anomaly and Change Point Detection |
Lecture 5 |
| 6 |
Anomalies in Sleep Monitoring + Deep Learning |
Lecture 6 |
| 7 |
Auto Encoders and DL for Health Care KPIs |
Lecture 7 |
| 8 |
Medical Imaging Use Cases |
Lecture 8 |
| 9 |
AI Methods for cancer diagnosis |
Lecture 9 |
| 10 |
Digital Scribing of Medical Records |
Lecture 10 |
| 11 |
NLP for Digital Scribing |
Lecture 11 |
| 12 |
Topic Modeling and Topic Segmentation |
Lecture 12 |
| 13 |
Interpretable models in Health Care |
Lecture 13 |
| 14 |
Interpretable and Explainable Models |
Lecture 14 |