This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (2847) JMIR Theme Issue: COVID-19 Special Issue (2500) Early Results from COVID-19 Studies (340) Machine Learning (1761) Clinical Information and Decision Making (1680) Decision Support for Health Professionals (1354) Outbreak and Pandemic Preparedness and Management (1783) Artificial Intelligence (1767) mHealth in a Clinical Setting (685) Design and Usability of Clinical Software and EHRs (304) Human Factors and Usability Case Studies (900) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1531) Infectious Diseases (non-STD/STI) (1659)

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

Authors of this article:

Ahmed Abdulaal1 Author Orcid Image ;   Aatish Patel1 Author Orcid Image ;   Ahmed Al-Hindawi1 Author Orcid Image ;   Esmita Charani2 Author Orcid Image ;   Saleh A Alqahtani3, 4 Author Orcid Image ;   Gary W Davies1 Author Orcid Image ;   Nabeela Mughal1, 2, 5 Author Orcid Image ;   Luke Stephen Prockter Moore1, 2, 5 Author Orcid Image
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JMIR Formative Res: Clinical Utility and Functionality of an artificial intelligence (#AI)–Based App to Predict Mor… https://t.co/QzLu2HDkgG

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RT @jmirpub: JMIR Formative Res: Clinical Utility and Functionality of an artificial intelligence (#AI)–Based App to Predict Mortality in #…

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Clinical Utility & Functionality of an #AI –Based App to Predict Mortality in #COVID19: Mixed Methods Analysis |… https://t.co/zIeRaQobQC

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