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Article

Scanning the medical phenome to identify new diagnoses after recovery from COVID-19 in a US cohort.

Journal of the American Medical Informatics Association : JAMIA - 18 Jan 2023

Kerchberger Vern Eric, Peterson Josh F, Wei Wei-Qi

Abstract excerpt

OBJECTIVE: COVID-19 survivors are at risk for long-term health effects, but assessing the sequelae of COVID-19 at large scales is challenging. High-throughput methods to efficiently identify new medical problems arising after acute medical events using the electronic health record (EHR) could improve surveillance for long-term consequences of acute medical problems like COVID-19. MATERIALS AND METHODS: We...

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Identifiers

PMID: 36005898
DOI: 10.1093/jamia/ocac159
PMCID: PMC9452157

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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