Biomedical Signal Extraction From Symptom Descriptions: An Observational Registry Using the OpenGenome Platform
Accuracy and Calibration of Evidence-Grounded Biomedical Signal Extraction From Free-Text Symptom Descriptions: A Prospective Observational Registry Using the OpenGenome Automated Research Instrument
OpenGenome
1,000 participants
May 5, 2026
OBSERVATIONAL
Conditions
Summary
This registry prospectively collects anonymized free-text symptom descriptions submitted voluntarily by adults through the OpenGenome platform at opengenome.bio. For each submission, the system retrieves real biomedical literature from PubMed and ClinicalTrials.gov in parallel, applies a constrained reasoning model operating under a strict output schema, and returns a structured biological signal report. The study evaluates the internal consistency of extracted signals, the calibration of confidence scores relative to dataset size and symptom specificity, and the distribution of biological signal categories across a large anonymous population. No intervention is assigned. No participant contact occurs. All data is anonymized at the point of collection.
Eligibility
Inclusion Criteria2
- Automated or programmatically generated submissions detected by rate limiting
- Submissions containing no discernible symptom or health-related content
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Interventions
AI-assisted biomedical signal extraction from free-text symptom descriptions, cross-referenced against PubMed and ClinicalTrials.gov evidence sources.
Locations(1)
View Full Details on ClinicalTrials.gov
For the most up-to-date information, visit the official listing.
NCT07578610