An AI Co-Data-Scientist for Prioritizing Candidate Biomarkers from Wearable Sensor Data

Abstract excerpt

<title>Abstract</title> <p>Wearable devices generate continuous physiological and behavioral data, but converting these signals into clinically reviewable biomarker hypotheses remains labor-intensive. We introduce CoDaS, an AI co-data-scientist that integrates multi-agent hypothesis generation, deterministic statistical analysis, adversarial validation and literature-grounded interpretation under human oversight....

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• Depression
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Identifiers and source

Literature Corpus work

8d2a99c5-c0e7-599c-8084-792ab471e288

DOI

10.21203/rs.3.rs-10063234/v1