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

Formative Evaluation of Digital Health Interventions (2503) Clinical Informatics (1051) Clinical Information and Decision Making (1442) Decision Support for Health Professionals (1216) Machine Learning (1511) Artificial Intelligence (1435) Electronic Health Records (1072)

Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46905, first published .
A Hybrid Decision Tree and Deep Learning Approach Combining Medical Imaging and Electronic Medical Records to Predict Intubation Among Hospitalized Patients With COVID-19: Algorithm Development and Validation

A Hybrid Decision Tree and Deep Learning Approach Combining Medical Imaging and Electronic Medical Records to Predict Intubation Among Hospitalized Patients With COVID-19: Algorithm Development and Validation

A Hybrid Decision Tree and Deep Learning Approach Combining Medical Imaging and Electronic Medical Records to Predict Intubation Among Hospitalized Patients With COVID-19: Algorithm Development and Validation

Authors of this article:

Kim-Anh-Nhi Nguyen1 Author Orcid Image ;   Pranai Tandon2 Author Orcid Image ;   Sahar Ghanavati1 Author Orcid Image ;   Satya Narayana Cheetirala1 Author Orcid Image ;   Prem Timsina1 Author Orcid Image ;   Robert Freeman1, 3 Author Orcid Image ;   David Reich3, 4 Author Orcid Image ;   Matthew A Levin4, 5, 6 Author Orcid Image ;   Madhu Mazumdar1, 7 Author Orcid Image ;   Zahi A Fayad8, 9 Author Orcid Image ;   Arash Kia1, 4 Author Orcid Image
Article Authors Cited by (7) Tweetations (3) Metrics

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  2. Kanber B, Smadi A, Noaman N, Liu B, Gou S, Alsmadi M. LightGBM: A Leading Force in Breast Cancer Diagnosis Through Machine Learning and Image Processing. IEEE Access 2024;12:39811 View
  3. Noaman N, Kanber B, Smadi A, Jiao L, Alsmadi M. Advancing Oncology Diagnostics: AI-Enabled Early Detection of Lung Cancer Through Hybrid Histological Image Analysis. IEEE Access 2024;12:64396 View
  4. Maia G, Martins C, Marques V, Christovam S, Prado I, Moraes B, Rezoagli E, Foti G, Zambelli V, Cereda M, Berra L, Rocco P, Cruz M, Samary C, Guimarães F, Silva P. Derivation and external validation of predictive models for invasive mechanical ventilation in intensive care unit patients with COVID-19. Annals of Intensive Care 2024;14(1) View
  5. Tsai M, Ko S, Huang A, Porta L, Ferretti C, Longhi C, Hsu W, Chang Y, Hsiung J, Su C, Galbiati F, Lee C. Predicting mortality in hospitalized influenza patients: integration of deep learning-based chest X-ray severity score (FluDeep-XR) and clinical variables. Journal of the American Medical Informatics Association 2024 View
  6. Grossbard E, Marziano Y, Sharabi A, Abutbul E, Berman A, Kassif-Lerner R, Barkai G, Hakim H, Segal G. Consensus Between Radiologists, Specialists in Internal Medicine, and AI Software on Chest X-Rays in a Hospital-at-Home Service: Prospective Observational Study. JMIR Formative Research 2024;8:e55916 View