Routine Laboratory Blood Tests Predict SARS-CoV-2 Infection Using Machine Learning

Abstract

Accurate diagnostic strategies to identify SARS-CoV-2 positive individuals rapidly for management of patient care and protection of health care personnel are urgently needed. The predominant diagnostic test is viral RNA detection by RT-PCR from nasopharyngeal swabs specimens, however the results are not promptly obtainable in all patient care locations. Routine laboratory testing, in contrast, is readily available with a turn-around time (TAT) usually within 1-2 hours.

Document Details

Document Type
Pub Defense Publication
Publication Date
Oct 30, 2020
Source ID
10.1093/clinchem/hvaa200

Entities

People

  • Amy Chadburn
  • Fei Wang
  • He S. Yang
  • Ljiljana V Vasovic
  • Massimo Loda
  • Melissa M Cushing
  • Peter A D Steel
  • Priya Velu
  • Rainu Kaushal
  • Sabrina E Racine-brzostek
  • Yu Hou
  • Zhen Zhao

Organizations

  • National Science Foundation
  • NewYork–Presbyterian Hospital
  • Office of Naval Research
  • Weill Cornell Medicine

Tags

Fields of Study

  • Medicine

Readers

  • Infectious Disease/Epidemiology
  • Oncology and Biomarker-Based Cancer Detection.
  • Systems Analysis and Design

Technology Areas

  • AI & ML