DaprTS - Deterministic NLP Pipeline to CDS

Deterministic, auditable NLP for transforming clinical notes into CDS-ready artifacts.

Why I Built This

Most clinical NLP systems feel like black boxes, which is risky when outputs influence care decisions or policy checks. I built DaprTS to turn unstructured notes into CDS-ready artifacts with deterministic steps that can be inspected and audited. The motivation was to make NLP outputs trustworthy enough for real clinical workflows, not just demos.

What I Implemented

  • A visible planner loop so every transformation step can be inspected.
  • Terminology grounding across SNOMED CT, LOINC, RxNorm, ICD-10-CM, and UCUM.
  • Strict $validate-code checks before accepting mapped concepts.
  • Structured outputs in JSON and CSV for downstream CDS use.

Stack

FastAPI + Streamlit with configurable terminology endpoints through config/terminology.yaml.

Outcome

A practical NLP-to-CDS bridge that is built for reviewability, not just one-off demos.