Work

Phenotyping coronavirus disease 2019 during a global health pandemic: Lessons learned from the characterization of an early cohort

Year: 2021

Type: article

Study design: Observational Study

Source: Journal of Biomedical Informatics

DOI: 10.1016/j.jbi.2021.103777

Authors: Sarah DeLozier, Harris T. Bland, Melissa McPheeters, Quinn Wells, Eric Farber-Eger, Cosmin A. Bejan, Daniel Fabbri, Trent Rosenbloom, Dan Roden, Kevin B. Johnson, Wei-Qi Wei, Josh Peterson, Lisa Bastarache

Institution: Vanderbilt University Medical Center

Language: English

Topic: Machine Learning in Healthcare

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: bronze

Funders: National Institutes of Health, National Heart, Lung, and Blood Institute, National Human Genome Research Institute, National Institute of General Medical Sciences, U.S. National Library of Medicine

Awards: Genomic and Phenomic Architecture of Heart Failure, Vanderbilt Genome-Electronic Records (VGER) Project, Initiative for Maximizing Student Development, Beyond PheWAS: Recognition of Phenotype Patterns for Discovery and Translation, The eMERGE Risk Assessment Network - Coordinating Center, PheMAP: Measured, Automated Profile to Facilitate High Throughput Phenotyping, Exploring Statin Pleiotropic Effects within a Very Large EHR Cohort

OpenAlex ID: W3152128110

FWCI: 0.791

Cites: 32

Cited by: 10

Related to: 10