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

Clinical Information and Decision Making (1423) JMIR Theme Issue: COVID-19 Special Issue (2458) Machine Learning (1488) Decision Support for Health Professionals (1201) Infectious Diseases (non-STD/STI) (1585) Tools, Programs and Algorithms (272) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1520) Outbreak and Pandemic Preparedness and Management (1739)

Published on in Vol 24, No 1 (2022): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/31549, first published .
The Development and Validation of Simplified Machine Learning Algorithms to Predict Prognosis of Hospitalized Patients With COVID-19: Multicenter, Retrospective Study

The Development and Validation of Simplified Machine Learning Algorithms to Predict Prognosis of Hospitalized Patients With COVID-19: Multicenter, Retrospective Study

The Development and Validation of Simplified Machine Learning Algorithms to Predict Prognosis of Hospitalized Patients With COVID-19: Multicenter, Retrospective Study

Authors of this article:

Fang He1, 2 Author Orcid Image ;   John H Page3 Author Orcid Image ;   Kerry R Weinberg2 Author Orcid Image ;   Anirban Mishra2 Author Orcid Image
Article Authors Cited by (17) Tweetations (3) Metrics

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  1. Buttia C, Llanaj E, Raeisi-Dehkordi H, Kastrati L, Amiri M, Meçani R, Taneri P, Ochoa S, Raguindin P, Wehrli F, Khatami F, Espínola O, Rojas L, de Mortanges A, Macharia-Nimietz E, Alijla F, Minder B, Leichtle A, Lüthi N, Ehrhard S, Que Y, Fernandes L, Hautz W, Muka T. Prognostic models in COVID-19 infection that predict severity: a systematic review. European Journal of Epidemiology 2023;38(4):355 View
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  4. Rasmy L, Nigo M, Kannadath B, Xie Z, Mao B, Patel K, Zhou Y, Zhang W, Ross A, Xu H, Zhi D. Recurrent neural network models (CovRNN) for predicting outcomes of patients with COVID-19 on admission to hospital: model development and validation using electronic health record data. The Lancet Digital Health 2022;4(6):e415 View
  5. Dong G, Jin F, Huang Q, Wu C, Zhu J, Wang T. Exploratory COVID-19 death risk score based on basic laboratory tests and physiological clinical measurements. World Journal of Emergency Medicine 2022;13(6):453 View
  6. Karpov O, Pitsik E, Kurkin S, Maksimenko V, Gusev A, Shusharina N, Hramov A. Analysis of Publication Activity and Research Trends in the Field of AI Medical Applications: Network Approach. International Journal of Environmental Research and Public Health 2023;20(7):5335 View
  7. Patton M, Liu V. Predictive Modeling Using Artificial Intelligence and Machine Learning Algorithms on Electronic Health Record Data. Critical Care Clinics 2023;39(4):647 View
  8. Banoei M, Rafiepoor H, Zendehdel K, Seyyedsalehi M, Nahvijou A, Allameh F, Amanpour S. Unraveling complex relationships between COVID-19 risk factors using machine learning based models for predicting mortality of hospitalized patients and identification of high-risk group: a large retrospective study. Frontiers in Medicine 2023;10 View
  9. Shi H, Yang J, Eom J, Ko J, Peck K, Kim U, Jung S, Kim S, Seok H, Hyun M, Kim H, Kim B, Joo E, Cheong H, Jun C, Wi Y, Kim J, Kym S, Lim S, Park Y. Clinical Characteristics and Risk Factors for Mortality in Critical COVID-19 Patients Aged 50 Years or Younger During Omicron Wave in Korea: Comparison With Patients Older Than 50 Years of Age. Journal of Korean Medical Science 2023;38(28) View
  10. Chimbunde E, Sigwadhi L, Tamuzi J, Okango E, Daramola O, Ngah V, Nyasulu P. Machine learning algorithms for predicting determinants of COVID-19 mortality in South Africa. Frontiers in Artificial Intelligence 2023;6 View
  11. Hiraga K, Takeuchi M, Kimura T, Yoshida S, Kawakami K. Prediction models for in-hospital deaths of patients with COVID-19 using electronic healthcare data. Current Medical Research and Opinion 2023;39(11):1463 View
  12. Miele L, Dajko M, Savino M, Capocchiano N, Calvez V, Liguori A, Masciocchi C, Vetrone L, Mignini I, Schepis T, Marrone G, Biolato M, Cesario A, Patarnello S, Damiani A, Grieco A, Valentini V, Gasbarrini A. Fib-4 score is able to predict intra-hospital mortality in 4 different SARS-COV2 waves. Internal and Emergency Medicine 2023;18(5):1415 View
  13. 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
  14. Le M, Davis M. ChatGPT Yields a Passing Score on a Pediatric Board Preparatory Exam but Raises Red Flags. Global Pediatric Health 2024;11 View
  15. González Rodríguez J, Oprescu A, Muñoz Lezcano S, Cordero Ramos J, Romero Cabrera J, Armengol de la Hoz M, Estella Á. Assessing the impact of vaccines on COVID-19 efficacy in survival rates: a survival analysis approach for clinical decision support. Frontiers in Public Health 2024;12 View
  16. Ceylan B, Olmuşçelik O, Karaalioğlu B, Ceylan Ş, Şahin M, Aydın S, Yılmaz E, Dumlu R, Kapmaz M, Çiçek Y, Kansu A, Duger M, Mert A. Predicting Severe Respiratory Failure in Patients with COVID-19: A Machine Learning Approach. Journal of Clinical Medicine 2024;13(23):7386 View

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