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

Decision Support for Health Professionals (1210) JMIR Theme Issue: COVID-19 Special Issue (2461) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1520)

Published on in Vol 8, No 10 (2020): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/21788, first published .
Predictive Models of Mortality for Hospitalized Patients With COVID-19: Retrospective Cohort Study

Predictive Models of Mortality for Hospitalized Patients With COVID-19: Retrospective Cohort Study

Predictive Models of Mortality for Hospitalized Patients With COVID-19: Retrospective Cohort Study

Authors of this article:

Taiyao Wang1, 2, 3 Author Orcid Image ;   Aris Paschalidis4 Author Orcid Image ;   Quanying Liu5 Author Orcid Image ;   Yingxia Liu6 Author Orcid Image ;   Ye Yuan7 Author Orcid Image ;   Ioannis Ch Paschalidis1, 2, 3 Author Orcid Image
Article Authors Cited by (13) Tweetations (5) Metrics

Journals

  1. Adamidi E, Mitsis K, Nikita K. Artificial intelligence in clinical care amidst COVID-19 pandemic: A systematic review. Computational and Structural Biotechnology Journal 2021;19:2833 View
  2. Wynants L, Van Calster B, Collins G, Riley R, Heinze G, Schuit E, Albu E, Arshi B, Bellou V, Bonten M, Dahly D, Damen J, Debray T, de Jong V, De Vos M, Dhiman P, Ensor J, Gao S, Haller M, Harhay M, Henckaerts L, Heus P, Hoogland J, Hudda M, Jenniskens K, Kammer M, Kreuzberger N, Lohmann A, Levis B, Luijken K, Ma J, Martin G, McLernon D, Navarro C, Reitsma J, Sergeant J, Shi C, Skoetz N, Smits L, Snell K, Sperrin M, Spijker R, Steyerberg E, Takada T, Tzoulaki I, van Kuijk S, van Bussel B, van der Horst I, Reeve K, van Royen F, Verbakel J, Wallisch C, Wilkinson J, Wolff R, Hooft L, Moons K, van Smeden M. Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal. BMJ 2020:m1328 View
  3. Abdulkareem K, Mostafa S, Al-Qudsy Z, Mohammed M, Al-Waisy A, Kadry S, Lee J, Nam Y, Chen M. Automated System for Identifying COVID-19 Infections in Computed Tomography Images Using Deep Learning Models. Journal of Healthcare Engineering 2022;2022:1 View
  4. Ramón A, Torres A, Milara J, Cascón J, Blasco P, Mateo J. eXtreme Gradient Boosting-based method to classify patients with COVID-19. Journal of Investigative Medicine 2022;70(7):1472 View
  5. Moslehi S, Mahjub H, Farhadian M, Soltanian A, Mamani M. Interpretable generalized neural additive models for mortality prediction of COVID-19 hospitalized patients in Hamadan, Iran. BMC Medical Research Methodology 2022;22(1) View
  6. Bottrighi A, Pennisi M, Roveta A, Massarino C, Cassinari A, Betti M, Bolgeo T, Bertolotti M, Rava E, Maconi A. A machine learning approach for predicting high risk hospitalized patients with COVID-19 SARS-Cov-2. BMC Medical Informatics and Decision Making 2022;22(1) View
  7. Yland J, Wang T, Zad Z, Willis S, Wang T, Wesselink A, Jiang T, Hatch E, Wise L, Paschalidis I. Predictive models of pregnancy based on data from a preconception cohort study. Human Reproduction 2022;37(3):565 View
  8. Shakibfar S, Nyberg F, Li H, Zhao J, Nordeng H, Sandve G, Pavlovic M, Hajiebrahimi M, Andersen M, Sessa M. Artificial intelligence-driven prediction of COVID-19-related hospitalization and death: a systematic review. Frontiers in Public Health 2023;11 View
  9. Casillas N, Ramón A, Torres A, Blasco P, Mateo J. Predictive Model for Mortality in Severe COVID-19 Patients across the Six Pandemic Waves. Viruses 2023;15(11):2184 View
  10. Faisal M, Mohammed M, Richardson D, Fiori M, Beatson K. Accuracy of automated computer-aided risk scoring systems to estimate the risk of COVID-19: a retrospective cohort study. BMC Research Notes 2024;17(1) View
  11. Al-Tam R, Hashim F, Maqsood S, Abualigah L, Alwhaibi R. Enhancing Parkinson’s Disease Diagnosis Through Stacking Ensemble-Based Machine Learning Approach. IEEE Access 2024;12:79549 View
  12. Bahrami A, Ghousi R, Atashi A, Barzinpour F. Presenting a Two-Stage Hybrid Model for Allocating Advanced Ventilators Using Machine Learning Methods: A Case Study. IEEE Access 2024;12:151317 View