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

Journals

  1. Puteri D, Buana P, Sukarsa I. Komparasi Metode Decision Tree dan Deep Learning dalam Meramalkan Jumlah Mahasiswa Drop Out Berdasarkan Nilai Akademik. Journal of Internet and Software Engineering 2024;1(2):12 View
  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