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

Theme Issue: Medical Informatics and COVID-19 (107) JMIR Theme Issue: COVID-19 Special Issue (2452) Decision Support for Health Professionals (1185) Imaging Informatics (193) Machine Learning (1465)

Published on in Vol 8, No 11 (2020): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/21604, first published .
Prediction of COVID-19 Severity Using Chest Computed Tomography and Laboratory Measurements: Evaluation Using a Machine Learning Approach

Prediction of COVID-19 Severity Using Chest Computed Tomography and Laboratory Measurements: Evaluation Using a Machine Learning Approach

Prediction of COVID-19 Severity Using Chest Computed Tomography and Laboratory Measurements: Evaluation Using a Machine Learning Approach

Authors of this article:

Daowei Li1 Author Orcid Image ;   Qiang Zhang2 Author Orcid Image ;   Yue Tan3 Author Orcid Image ;   Xinghuo Feng4 Author Orcid Image ;   Yuanyi Yue3 Author Orcid Image ;   Yuhan Bai5 Author Orcid Image ;   Jimeng Li6 Author Orcid Image ;   Jiahang Li6 Author Orcid Image ;   Youjun Xu7 Author Orcid Image ;   Shiyu Chen8 Author Orcid Image ;   Si-Yu Xiao9 Author Orcid Image ;   Muyan Sun9 Author Orcid Image ;   Xiaona Li10 Author Orcid Image ;   Fang Zhu11 Author Orcid Image
Article Authors Cited by (15) Tweetations (1) Metrics

Journals

  1. Islam M, Poly T, Alsinglawi B, Lin M, Hsu M, Li Y. A State-of-the-Art Survey on Artificial Intelligence to Fight COVID-19. Journal of Clinical Medicine 2021;10(9):1961 View
  2. Moezzi M, Shirbandi K, Shahvandi H, Arjmand B, Rahim F. The diagnostic accuracy of Artificial Intelligence-Assisted CT imaging in COVID-19 disease: A systematic review and meta-analysis. Informatics in Medicine Unlocked 2021;24:100591 View
  3. Guo Y, Zhang Y, Lyu T, Prosperi M, Wang F, Xu H, Bian J. The application of artificial intelligence and data integration in COVID-19 studies: a scoping review. Journal of the American Medical Informatics Association 2021;28(9):2050 View
  4. Laino M, Ammirabile A, Posa A, Cancian P, Shalaby S, Savevski V, Neri E. The Applications of Artificial Intelligence in Chest Imaging of COVID-19 Patients: A Literature Review. Diagnostics 2021;11(8):1317 View
  5. Laino M, Ammirabile A, Lofino L, Lundon D, Chiti A, Francone M, Savevski V. Prognostic findings for ICU admission in patients with COVID-19 pneumonia: baseline and follow-up chest CT and the added value of artificial intelligence. Emergency Radiology 2022;29(2):243 View
  6. Singh V, Kamaleswaran R, Chalfin D, Buño-Soto A, San Roman J, Rojas-Kenney E, Molinaro R, von Sengbusch S, Hodjat P, Comaniciu D, Kamen A. A deep learning approach for predicting severity of COVID-19 patients using a parsimonious set of laboratory markers. iScience 2021;24(12):103523 View
  7. Bakhtiarvand N, Khashei M, Mahnam M, Hajiahmadi S. A novel reliability-based regression model to analyze and forecast the severity of COVID-19 patients. BMC Medical Informatics and Decision Making 2022;22(1) View
  8. Gusev A, Vladzimirskiy A, Gavrilenko G. Methodical approach and recommendations for scientific description of creation and validation of machine learning model. Medical Technologies. Assessment and Choice 2022;(3):12 View
  9. Ortiz S, Rojas F, Valenzuela O, Herrera L, Rojas I. Determination of the Severity and Percentage of COVID-19 Infection through a Hierarchical Deep Learning System. Journal of Personalized Medicine 2022;12(4):535 View
  10. Li Q, An Z, Pan Z, Wang Z, Wang Y, Zhang X, Shen N. Severe/critical COVID-19 early warning system based on machine learning algorithms using novel imaging scores. World Journal of Clinical Cases 2023;11(12):2716 View
  11. Viderman D, Kotov A, Popov M, Abdildin Y. Machine and deep learning methods for clinical outcome prediction based on physiological data of COVID-19 patients: a scoping review. International Journal of Medical Informatics 2024;182:105308 View
  12. Pravin S, Rohith G, V K, Saranya J, Latha B, Vigneshwar K, Krishna S, Nambirajan H, Sumitra Y. PixNet for early diagnosis of COVID-19 using CT images. Multimedia Tools and Applications 2024 View
  13. Hamar Á, Mohammed D, Váradi A, Herczeg R, Balázsfalvi N, Fülesdi B, László I, Gömöri L, Gergely P, Kovacs G, Jáksó K, Gombos K. COVID-19 mortality prediction in Hungarian ICU settings implementing random forest algorithm. Scientific Reports 2024;14(1) View

Books/Policy Documents

  1. Qi X, Shen L, Chen J, Shi M, Shen B. Translational Informatics. View