| 1 | 9/3 | Intro to class (Lab 0) | 9/5 | What’s different in health? modalities, imbalance, rare events, stakeholders, etc. |
| 2 | 9/10 | Intro to clinical care and understanding clinical data | 9/12 | Classification methods in healthcare: diagnosis, prognosis, segmentation (MP1 - omics) |
| 3 | 9/17 | SVM, random forests, XGBoost: interpretation of different model choices | 9/19 | Unsupervised methods for healthcare: subtype discovery, pattern discovery |
| 4 | 9/24 | PCA, ICA, tensor decomposition | 9/26 | Clustering methods (MP2 – physiological signals) |
| 5 | 10/1 | Causal Inference in Healthcare (Deadline to form project groups) | 10/3 | Deep learning for healthcare: Intro |
| 6 | 10/8 | Digital health (Guest Lecture - Prof. Srivastava) | 10/10 | ConvNets & PyTorch tutorial (MP3 - medical imaging) |
| 7 | 10/15 | CNNs for medical imaging and signals | 10/17 | (Project proposals & Mini project release) |
| 8 | 10/22 | Explanations and attributions | 10/24 | Graphs and Networks in Healthcare |
| 9 | 10/29 | Graph ML & Healthcare Applications | 10/31 | Sequence modeling in healthcare - Part I |
| 10 | 11/5 | Sequence modeling in healthcare - Part II | 11/7 | AI in Medical Device Industry (Guest Lecture - Medtronic) (Project mid-term reports) |
| 11 | 11/12 | Unsupervised deep learning for healthcare, self-supervised learning | 11/14 | Clinical foundation models |
| 12 | 11/19 | Medical AI evaluation and deployment | 11/21 | Ethical AI for healthcare (Guest Lecture - Mayo Clinic)(Mini project due) |
| 13 | 11/26 | Medical AI model robustness | 11/28 | Thanksgiving |
| 14 | 12/3 | Uncertainty Quantification | 12/5 | Fairness in Medical AI |
| 15 | 12/10 | Project presentations | EOS | Reports due |