Healthcare Ml
2 long-form posts on Healthcare Ml: machine-learning research by Taha Bouhsine, each built around live, in-browser interactive visualizations.
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Running the Survival Trial, in JAX/Flax NNX
Build the Yat DeepSurv trunk and Cox loss in Flax NNX, recover exact prototype contributions and explicit row edits, then run the LR-fair five-dataset benchmark with concordance, calibration, Brier, AUC, and classical baselines.
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The White-Box Survival Model on Trial
Build a survival network from learned prototype patients, derive its exact risk decomposition, and benchmark it on five datasets against Cox, penalized Cox, Random Survival Forest, and ReLU DeepSurv. Calibration, editing, and shift detection are measured separately.