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HST.953 | Fall 2024 | Graduate

# Clinical Data Learning, Visualization, and Deployments

### Weekly Reflections

As explained in the syllabus, the weekly reflections, corresponding to weeks 2–10, will be done as a discussion via the internal class website, and are due before class. For each week, reflect on one of that week’s papers, and specifically call out 5 things:

1. Problem being addressed
2. Contribution made
3. Evaluation used
4. Your opinion on whether its a meaningful contribution
5. The “secret terrible thing” about the paper

### Problem Sets

Due dates for each problem set are noted within the file, and in the course calendar.

Problem Set 1 (PDF)

Problem Set 1 IPython notebook (.ipynb)

Problem Set 2 (PDF)

Problem Set 2 IPython notebook (.ipynb)

Problem Set 3 (PDF)

## Course Info

##### Instructors

- Marzyeh Ghassemi
- Leo A Celi
- Adam Rodman
- Ned McCague

##### Departments

- Electrical Engineering and Computer Science
- Health Sciences and Technology

##### As Taught In

Fall 2024

##### Level

Graduate

##### Topics

- Engineering
  - Computer Science
    - Artificial Intelligence
- Health and Medicine

##### Learning Resource Types

assignment Problem Sets
assignment Programming Assignments
auto_stories Readings

Browse Resources

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