This framework is an open research / clinical decision-support prototyping toolkit. It is not a regulated medical device.
Questions or feedback: support@larucare.com · docs/HOW_IT_HELPS.md
- Not for diagnosis, treatment, or triage without institutional governance
- No FDA/CE claim; outputs are research probabilities only
- User is responsible for PHI, IRB, DUA, and PhysioNet rules
- Local API is unsafe on public networks without
API_KEY - Clinical-research mode is a prototype, not production CDS
- Canonical path: tabular/longitudinal events → window aggregates
- Not full free-text NLP, imaging, waveforms, or genomics
- FHIR/OMOP adapters are subset importers, not full CDM/FHIR servers
- MIMIC requires user credentials; restricted data is never shipped
- Schema mapping cannot fix wrong labels or upstream leakage
- Default upload size limit ~50MB
- SQL import is read-only
SELECT/WITH … SELECT
- Supported: logistic regression, random forest, XGBoost, optional LightGBM
- LSTM / Transformers / foundation models: not supported
- Multi-model compare ranks by hold-out ROC-AUC — not full AutoML/HPO
- Tiny cohorts → unstable or undefined AUC (framework warns)
- Calibration improves probability quality; does not guarantee clinical utility
- SHAP explains the fitted model — not causal effects
- Default splits are research hold-outs; multi-site validation is user-provided
- Fairness requires group columns; otherwise skipped with an explicit reason
- Leakage audit catches common classes — not every contamination pattern
- Synthetic results are for method/CI verification — not clinical performance claims
- Single-host research workbench; not multi-tenant SaaS
- One heavy job at a time (not a cluster scheduler)
- Filesystem experiment runs — not a full MLflow/W&B replacement
- No Model Hub / community marketplace in this release
- Windows/macOS ease depends on Docker Desktop
- User backs up
reports/runs/and config
- Configurable: tasks, windows, horizon, splits, models, calibrate, persona
- Formal plugin marketplace not included
- Advanced feature engineering beyond YAML may require Python changes
We do not claim to:
- Solve all healthcare AI
- Replace hospital EHR systems
- Be state-of-the-art on every MIMIC benchmark
- Be “bias-free” or to have “solved fairness”