ClarusC64/clinical-quad-biomarker-drift-dose-intensity-comed-burden-inflammation-ae-escalation-v0.1
What this repo does This dataset models adverse event escalation as a basin shift in patient state space. It predicts when the interaction between biomarker drift, dose intensity, comedication burden, and inflammation signal pushes a patient into an adverse event escalation regime. Core quad biomarker_drift_index dose_intensity_index comedication_burden_index inflammation_marker_index Prediction target label_ae_escalation Row structure Each row represents a patient monitoring snapshot during… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-biomarker-drift-dose-intensity-comed-burden-inflammation-ae-escalation-v0.1.
What this repo does
This dataset models adverse event escalation as a basin shift in patient state space. It predicts when the interaction between biomarker drift, dose intensity, comedication burden, and inflammation signal pushes a patient into an adverse event escalation regime.
Core quad
biomarkerdriftindex doseintensityindex comedicationburdenindex inflammationmarkerindex
Prediction target
labelaeescalation
Row structure
Each row represents a patient monitoring snapshot during active treatment. The model predicts whether the coupled physiologic drift and treatment pressure produce an adverse event escalation within the next monitoring window.
Files
data/train.csv data/tester.csv scorer.py
Evaluation
Run predictions on tester.csv Add column prediction Score with scorer.py
License
MIT
Structural Note
This dataset identifies a measurable coupling pattern associated with systemic instability. The sample demonstrates the geometry. Production-scale data determines operational exposure.
What Production Deployment Enables
• 50K–1M row datasets calibrated to real operational patterns • Pair, triadic, and quad coupling analysis • Real-time coherence monitoring • Early warning before cascade events • Collapse surface and recovery window modeling • Integration and implementation support
Small samples reveal structure. Scale reveals consequence.
Enterprise & Research Collaboration
Clarus develops production-scale coherence monitoring infrastructure for critical systems across healthcare, finance, infrastructure, and regulatory domains.
For dataset expansion, custom coherence scorers, or deployment architecture: team@clarusinvariant.com
Instability is detectable. Governance determines whether it propagates.