[dalloliogm]

Hello,

Almost one year ago I started contributing to the VAE bounty in PyHealth. Unfortunately, I messed up with Git and became busy with work, and time passed, so I never followed up on the review comments on my previous PR.

This is a new implementation of the bounty for PyHealth 2.0.

Contributor: Giovanni Dall’Olio

Contribution Type: Model

Description: The VAE now supports image inputs and categorical EHR code sequences. I’ve also added or updated three notebooks demonstrating synthetic image generation, ChestXray14 image modeling, and EHR sequence modeling, with explanations of potential applications.

Files to Review:

• pyhealth/models/vae.py - VAE implementation for image and categorical sequence inputs.
• tests/core/test_vae.py - model behavior, generation, and Trainer compatibility tests.
• examples/cxr/vae_cxr_synthetic.ipynb - synthetic image VAE example.
• examples/cxr/vae_cxr_chestxray14.ipynb - ChestXray14 image example.
• examples/mortality_prediction/vae_ehr_sequences.ipynb - EHR sequence example.
• examples/cxr/chextXray_image_generation_VAE.py - updated image VAE example.
• docs/tutorials.rst and docs/api/models/pyhealth.models.VAE.rst - tutorial links and API documentation.

[github-actions]

Test Coverage

Total: 74.07% (20432 / 27585 lines)

Modified file	Coverage	Lines
pyhealth/models/vae.py	88.29%	181 / 205

Workflow run · 56bbdec

[jhnwu3]

/review

[github-actions]

AI Review

suggestion: not available
decision: human review

This PR is too large for AI review (over 300 files or 200000 diff characters), so it is labeled status: manual and needs a human review.

[dalloliogm]

If the PR is too large, I can split it into two, so the AI review can take place.

The changes to the VAE class are small. Most of the new lines come from the notebooks included to describe what is a VAE and how it can be used. I could split those into a different PR