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

Digital Health Reviews (1530) Decision Support for Health Professionals (1342) Machine Learning (1742) Clinical Information and Decision Making (1661) Artificial Intelligence (1748)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46340, first published .
Diagnostic Test Accuracy of Deep Learning Prediction Models on COVID-19 Severity: Systematic Review and Meta-Analysis

Diagnostic Test Accuracy of Deep Learning Prediction Models on COVID-19 Severity: Systematic Review and Meta-Analysis

Diagnostic Test Accuracy of Deep Learning Prediction Models on COVID-19 Severity: Systematic Review and Meta-Analysis

Authors of this article:

Changyu Wang1, 2 Author Orcid Image ;   Siru Liu3 Author Orcid Image ;   Yu Tang4 Author Orcid Image ;   Hao Yang5 Author Orcid Image ;   Jialin Liu1, 5 Author Orcid Image
Article Authors Cited by (3) Tweetations (5) Metrics

Journals

  1. Melo V, do Brasil P. ACCREDIT: Validation of clinical score for progression of COVID-19 while hospitalized. Global Epidemiology 2025;9:100181 View
  2. Rakovics M, Meznerics F, Fehérvári P, Kói T, Csupor D, Bánvölgyi A, Rapszky G, Engh M, Hegyi P, Harnos A. Deep neural networks excel in COVID-19 disease severity prediction—a meta-regression analysis. Scientific Reports 2025;15(1) View
  3. Iwasaki T, Arimura H, Inui S, Kodama T, Cui Y, Ninomiya K, Iwanaga H, Hayashi T, Abe O. Predictive models of severe disease in patients with COVID-19 pneumonia at an early stage on CT images using topological properties. Radiological Physics and Technology 2025;18(2):534 View