Published on in Vol 10 , No 4 (2022) :April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38505, first published .
Correction: Mining Electronic Health Records for Drugs Associated With 28-day Mortality in COVID-19: Pharmacopoeia-wide Association Study (PharmWAS)

Correction: Mining Electronic Health Records for Drugs Associated With 28-day Mortality in COVID-19: Pharmacopoeia-wide Association Study (PharmWAS)

Correction: Mining Electronic Health Records for Drugs Associated With 28-day Mortality in COVID-19: Pharmacopoeia-wide Association Study (PharmWAS)

Ivan Lerner 1, 2, 3 , MD ;   Arnaud Serret-Larmande 1, 2 , MD ;   Bastien Rance 1, 3 , PhD ;   Nicolas Garcelon 3, 4 , PhD ;   Anita Burgun 1, 2, 3 , MD, PhD ;   Laurent Chouchana 5 , PhD, PharmD ;   Antoine Neuraz 1, 2, 3 , MD, PhD

1 Inserm , Centre de Recherche des Cordeliers , Sorbonne Université , Paris , FR

2 Informatique biomédicale , Hôpital Necker-Enfants Malades , Assistance Publique - Hôpitaux de Paris , Paris , FR

3 HeKA Team , Inria , Paris , FR

4 Inserm UMR 1163 , Data Science Platform , Université de Paris, Imagine Institute , Paris , FR

5 Centre Régional de Pharmacovigilance , Service de Pharmacologie, Hôpital Cochin , Assistance Publique - Hôpitaux de Paris, Centre - Université de Paris , Paris , FR

Corresponding Author:

  • Antoine Neuraz, MD, PhD
  • Inserm
  • Centre de Recherche des Cordeliers
  • Sorbonne Université
  • Université de Paris
  • 15 Rue de l'École de Médecine
  • Paris
  • FR
  • Phone: 33 01 44 27 64 82
  • Email: antoine.neuraz@aphp.fr