2026-09-20T23:22:28.549Z
- publishedAt:
Not provided→ 2021-03-15T00:00:00.000Z
SOURCE-LINKED INTELLIGENCE
COVID-19 Detection and Prognostication Models Allegedly Flagged for Methodological Flaws and Underlying Biases
Peer-review of papers about COVID-19 detection and prognostication algorithms from 2020, including deployed models, revealed none to be ready for clinical use, due to methodological flaws and underlying biases such as lacking external validation or not specifying data sources and model training details.
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- recordType
- incident-report
- evidenceStatus
- reported
- region
- Global
Reported occurrence date: 2020-01-01T00:00:00.000Z
Evidence & attribution
- AI Incident Database
- AI Incident Database · 2021-03-15T00:00:00.000Z
AI Incident Database, Responsible AI Collaborative; McGregor (2021), Preventing Repeated Real World AI Failures by Cataloging Incidents. Incident-specific contributor credits are available at each citation link. Metadata adapted; article text excluded.
License: CC BY-SA 4.0
First collected: 2026-09-19T22:50:59.123Z. This is not the publication date.
Observed changes
AIIC observation times, not verified publisher revision times. Up to eight recent revisions.