Published on in Vol 5, No 7 (2021): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27992, first published .
Clinical Utility and Functionality of an Artificial Intelligence–Based App to Predict Mortality in COVID-19: Mixed Methods Analysis

Clinical Utility and Functionality of an Artificial Intelligence–Based App to Predict Mortality in COVID-19: Mixed Methods Analysis

Clinical Utility and Functionality of an Artificial Intelligence–Based App to Predict Mortality in COVID-19: Mixed Methods Analysis

Ahmed Abdulaal   1 , MBBS, MRCS ;   Aatish Patel   1 , MBChB, MRCP ;   Ahmed Al-Hindawi   1 , MBBS, MRCA ;   Esmita Charani   2 , MPharm, PhD ;   Saleh A Alqahtani   3, 4 , MD ;   Gary W Davies   1 , MD, FRCP ;   Nabeela Mughal   1, 2, 5 , BSc, MSc, MRCP, FRCPath ;   Luke Stephen Prockter Moore   1, 2, 5 , MBChB, DTM&H, MSc, MPH, PhD, MRCP, FRCPath

1 Chelsea and Westminster NHS Foundation Trust, London, United Kingdom

2 National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, United Kingdom

3 Johns Hopkins University, Baltimore, MD, United States

4 King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia

5 North West London Pathology, Imperial College Healthcare NHS Trust, London, United Kingdom

Corresponding Author:

  • Luke Stephen Prockter Moore, MBChB, DTM&H, MSc, MPH, PhD, MRCP, FRCPath
  • National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance
  • Imperial College London
  • Commonwealth Building 8th Floor
  • Du Cane Road
  • London, W12 0NN
  • United Kingdom
  • Phone: 44 2033158273
  • Email: l.moore@imperial.ac.uk