LibraryFamily 17 · Research & Clinical Trials
Clinical trial recruitment matching
CuratedPilotEmerging evidence
Reviewed for completeness and published to the Library.
Screens structured records and clinical notes against trial eligibility criteria to surface a ranked list of candidate patients for the research team.
Plain-language summary
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Clinical context
- Clinical problem
- Discover a research insight
- Point of care
- Back office
- Nature of AI output
- A prioritised list
- Clinical specialty
- Oncology
- Care setting
- Back office
- Patient population
- Patients potentially eligible for open oncology clinical trials at the cancer centre.
- Intended use
- Screens structured records and clinical notes against trial eligibility criteria to surface a ranked list of candidate patients for the research team.
Technology
- AI technique
- NLP / large language model, Classical machine learning
- Input data
- Structured EHR data, Clinical notes / free text
- Output type
- Prioritisation / schedule
- Autonomy level
- Informs a human (advisory)
- Model provenance
- Research model
- Model version
- —
- Built on a general-purpose model
- Yes
Deployment
- Status
- Pilot
- Country
- Netherlands
- Deployment date
- 1 February 2025
- Sites
- 1
Regulatory & governance
- EU AI Act risk tier
- Minimal risk
- High-risk basis
- Not applicable
- Medical device
- No
- EU MDR class
- Not a device
- CE marking
- Not required
- FDA status
- Not applicable
- ISO 14971 risk class
- Low
- GDPR processing basis
- Public interest
- GDPR DPIA
- Completed
- Data identifiability
- Pseudonymised
- Explainability method
- Post-hoc
- Human oversight model
- The research team verifies eligibility and obtains consent; AI only prioritises candidates.
NICE evidence standards
- ESF tier
- Tier A — system / service
- Evidence category
- —
Performance summary
- Headline metric
- Positive predictive value
- Value
- 0.74
- Subgroup performance assessed
- No
- Known bias signals
- —
Similar deployments
AILooking for close matches in the Library…
Evidence records
Studies and evaluations attached to this use case.
Retrospective validation
Positive predictive value: 0.74
Population: Oncology trial screening cohort
Contributors
- Deploying organisation
- [demo] Erasmus MC · Hospital / health system · Netherlands
- AI vendor
- [demo] TU Delft — AIH Lab · Netherlands
- Product name
- —