Clinical case development
Authoring of diagnostic scenarios, longitudinal lab panels, atypical presentations, and multi-system pathology cases engineered to elicit specific failure modes in state-of-the-art models.
case design / golden responsesClinical evaluation. Under NDA.
The clinical eval layer for medical AI.
242 Academia LLC partners with medical AI teams on clinical case development, evaluation rubric design, expert annotation, and model performance review. Physician-led. NDA-first. Available for new engagements.
What we do.
Four services. One bar: clinical rigor delivered under NDA. Each engagement is scoped against your model class, eval framework, and timeline.
Evaluation rubrics and frameworks
Rubric design with criteria atomicity, stacking prevention, weighted scoring (binary and graded), and negative-criterion construction for objective AI response grading.
rubric engineeringExpert annotation and data quality review
Calibrated annotation across clinical reasoning tasks. Quality assurance for physician writer pods. Standardized error classification with guideline-referenced reasoning.
annotation / QAAI model performance evaluation
Benchmarking and red-teaming for clinical AI applications. Failure-mode taxonomies. Paired-response scoring with justification documentation.
benchmarks / red-teamHow we work.
A short methodology. The same principles every engagement.
- Atomicity
- Each rubric criterion tests one thing, with binary scoring and explicit failure conditions. No stacked criteria, no subjective wording.
- Calibrated scoring
- Weighted frameworks tuned for clinical relevance, not vibes. Graded scales (commonly negative-ten to positive-ten) with documented anchor points.
- Golden response authoring
- Reference answers built from guideline-referenced clinical reasoning, with citations to specialty society guidance where applicable.
- Failure-mode taxonomy
- Documented patterns of how clinical AI breaks: sequential lab misinterpretation, deterioration trajectory misreading, multi-layer lab synthesis errors, atypical presentation handling.
- NDA-first
- Every engagement begins with mutual NDA before any clinical artifact, prompt, or model output is exchanged. Client identity is never disclosed externally.
At a glance.
What you can expect, said plainly.
- Active.Engagements with leading medical AI labs and platforms. Accepting new projects on a rolling basis.
- Board-certified.Physician principal on every engagement. Generalist clinical reasoning capacity.
- Tooling.Familiarity with frontier model APIs (Anthropic Claude, OpenAI), Epic EMR (SlicerDicer, SmartPhrases, dot phrases), and ICD-10 / E/M / CPT coding.
- Confidentiality.Engagements under NDA. Client names withheld by design.
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