Machine learning identifies long COVID patterns from electronic health records

Nat Med. 2023 Jan;29(1):47-48. doi: 10.1038/s41591-022-02130-5.

Abstract

A machine learning algorithm identifies four reproducible clinical subphenotypes of long COVID from the electronic health records of patients with post-acute sequelae of SARS-CoV-2 infection within 30–180 days of infection; these patterns have implications for the treatment and management of long COVID.

Publication types

  • Comment

MeSH terms

  • COVID-19* / epidemiology
  • Electronic Health Records
  • Humans
  • Machine Learning
  • Post-Acute COVID-19 Syndrome
  • SARS-CoV-2