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Self-Explaining Hypergraph Neural Networks for Diagnosis Prediction.#1033

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nmuralikrishnan wants to merge 4 commits intosunlabuiuc:masterfrom
ssharif6:master
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Self-Explaining Hypergraph Neural Networks for Diagnosis Prediction.#1033
nmuralikrishnan wants to merge 4 commits intosunlabuiuc:masterfrom
ssharif6:master

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PR description must include all of the following:

  • Contributors: Murali Natarajan (muralin2), Joshua Jiang (joshuaj9), Shaheen Sharifian (ssharif2)
  • Type: Model contribution
  • Paper link: https://proceedings.mlr.press/v287/yu25a.html
  • High-level description: SHy implements self-explaining diagnosis prediction using per-patient hypergraphs, UniGIN message passing, temporal phenotype extraction via Gumbel-Softmax, and a multi-objective loss
  • File guide:
    • pyhealth/models/shy.py — Core model implementation (SHy, SHyLayer, all subcomponents)
    • pyhealth/models/__init__.py — Added SHy export
    • tests/core/test_shy.py — 15 unit tests with synthetic data
    • docs/api/models/pyhealth.models.SHy.rst — RST autodoc
    • docs/api/models.rst — Added SHy to index
    • examples/mimic3_diagnosis_prediction_shy.py — Ablation study script

ssharif6 and others added 4 commits April 4, 2026 23:47
…is Prediction

Implements the SHy model from Yu et al. (CHIL 2025) as a PyHealth BaseModel.
SHy uses per-patient hypergraphs with UniGIN message passing and temporal
phenotype extraction for interpretable diagnosis prediction.

Paper: https://proceedings.mlr.press/v287/yu25a.html

Files added/modified:
- pyhealth/models/shy.py: Core model implementation
- pyhealth/models/__init__.py: Added SHy export
- tests/core/test_shy.py: Functional test verifying model trains
- docs/api/models/pyhealth.models.SHy.rst: Documentation
- docs/api/models.rst: Added to index
- examples/mimic3_diagnosis_prediction_shy.py: Ablation study
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3 participants