ModelRefs / Clinical Trial Matching — Canonical Workflow

Clinical Trial Matching — Canonical Workflow

Clinical Trial Matching: provisional AI workflow implementation reference with candidate models, providers, tools, and architecture.

Overview

Screen authorized patient data against versioned trial criteria to prepare candidate matches and missing-data flags for coordinator and investigator review; eligibility and enrollment are not determined. Healthcare deployment requires organization- and jurisdiction-specific review of privacy, security, access, retention, and applicable regulatory obligations. Outputs remain provisional and require qualified human review; no clinical autonomy or compliance claim is implied. Validate PHI flows, source traceability, model and prompt versions, reviewer actions, rollback, and incident handling before clinical use.

Implementation profile

Categoryllms
Implementation maturityenterprise
Primary use casesrag, extraction
Deployment optionsmanaged-api, hybrid
Architecturesserverless-api, managed-container, hybrid-private-cloud

What this evidence does not establish

  • No disease area, trial inventory, site geography, patient schema, terminology map, consent basis, coordinator process, or acceptance threshold is registered.
  • No measured criterion accuracy, candidate recall, false-match rate, missed-match rate, review burden, or enrollment outcome is attached.

Candidate models with published references

Coverage means the model is a candidate worth evaluating for this workflow, not a ranking or a recommendation. Models whose reference pages are still in review are omitted.

Benchmarks relevant to this workflow

  • GPQA Diamond — Graduate-level Google-Proof Q&A in physics, chemistry, and biology.
  • MMLU-Pro — Harder MMLU successor with 10-option questions and reduced contamination.
  • MMLU — Massive Multitask Language Understanding — 57 academic and professional subjects.

These are the benchmarks whose task shape bears on this workflow. Each one only describes its own protocol and date, so confirm the harness matches your workload before treating a score as evidence.

Continue your research

Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to Clinical Trial Matching — Canonical Workflow.