Selected Projects

A selection of clinically grounded AI systems and data science projects, focused on medical imaging, risk stratification, and decision support.

Anesthesia Drift Detector

A monitoring pipeline to detect distributional drift in anesthesia-related physiological signals, enabling early warnings when model assumptions degrade in real-world clinical settings.

  • Time-series monitoring & drift detection
  • Clinical safety & model reliability
  • Python, statistical monitoring, visualization
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HCC Extractor (Hierarchical Condition Category)

A hybrid NLP and rule-based system that derives ICD-10 diagnosis codes from unstructured clinical text and maps them to Hierarchical Condition Categories (HCCs) for risk adjustment and analytics.

  • Pipeline: Clinical text → ICD-10 → HCC mapping
  • NLP + rule-based extraction
  • Healthcare coding & structured data generation
  • Python, text processing, validation logic

PinkScan AI

A non-invasive breast health screening concept combining imaging signals with AI-driven decision support to enable scalable early screening workflows in resource-constrained settings.

  • Clinical screening & triage support
  • Imaging-based inference
  • Model prototyping & evaluation