Biomedical Signal Extraction From Symptom Descriptions: An Observational Registry Using the OpenGenome Platform

Condition(s) studied

Investigational drug(s) / intervention(s)

OpenGenome AI Platform: AI-assisted biomedical signal extraction from free-text symptom descriptions, cross-referenced against PubMed and ClinicalTrials.gov evidence sources.

Study 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

Primary outcome measure(s)

• Internal signal-source concordance rate — At point of automated report generation, assessed continuously over 12 months
  Proportion of primary signal claims in generated reports that are traceable to at least one retrieved PubMed or ClinicalTrials.gov source included in the same report

Trial sites (1)

Other trials for the same condition