- Reviewed the package as a supervisor-ready research scaffold rather than a finished medical AI system.
- Identified key gaps: real feature extraction, MONAI training, patient-level split enforcement, and external validation.
- Refined the runnable baseline so it creates cross-validation predictions and real evaluation metrics.
- Added GitHub hygiene with
.gitignore, CI, reproducibility notes, and upload safety checklist. - Confirmed the scaffold pipeline runs end to end with demo features after installing pinned dependencies.
- Added a public-data test path using the UCI Vertebral Column dataset for non-patient, tabular viability testing.
- Added a public imaging dataset strategy covering MURA, RSNA Cervical Spine on Kaggle, VerSe, CTSpine1K, TCIA/NBIA, and NIH ChestX-ray14 caveats.
Use this repository first to prove reproducible CLI/Colab execution. Treat demo and public tabular tests as engineering checks only. Thesis claims still require a narrowed research question, real de-identified features, ethics approval for local data, and patient-level validation.