Improved real-time surveillance of COVID-19 patients' electronic health records using transfer learning and ordinal regression
- Funded by University of Michigan
- Total publications:0 publications
Grant number: unknown
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Key facts
Disease
COVID-19Start & end year
N/AKnown Financial Commitments (USD)
$0Funder
University of MichiganResearch Location
United States of AmericaLead Research Institution
N/AResearch Priority Alignment
N/A
Research Category
Epidemiological studiesResearch Subcategory
Impact/ effectiveness of control measuresSpecial Interest Tags
Digital HealthStudy Type
UnspecifiedClinical Trial Details
N/ABroad Policy Alignment
PendingAge Group
UnspecifiedVulnerable Population
UnspecifiedOccupations of Interest
Unspecified
Abstract
Led by Drs. Andrew Admon (Internal Medicine) and Christopher Gillies (Emergency Medicine), this team is using Machine Learning, a powerful data science tool, to build a real-time patient surveillance system. During times of unprecedented strain on healthcare personnel and clinical resources, this will help clinicians identify COVID-19 patients who need more intensive monitoring, closer nursing care, or urgent physician intervention.