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

Artificial Intelligence (1371) JMIR Theme Issue: COVID-19 Special Issue (2452) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1517) Secondary Use of Clinical Data for Research and Surveillance (367) Systemic Racism and Racial Bias in Health Care and Society (85) Innovative Methods in Public Health and Surveillance (332) Infectious Diseases (non-STD/STI) (1575) Information Models (28) Clinical Information and Decision Making (1407) Clinical Informatics (1022) Machine Learning (1465) E-Health / Health Services Research and New Models of Care (517)

Published on in Vol 23, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/31337, first published .
Predicting COVID-19–Related Health Care Resource Utilization Across a Statewide Patient Population: Model Development Study

Predicting COVID-19–Related Health Care Resource Utilization Across a Statewide Patient Population: Model Development Study

Predicting COVID-19–Related Health Care Resource Utilization Across a Statewide Patient Population: Model Development Study

Authors of this article:

Suranga N Kasturi1, 2 Author Orcid Image ;   Jeremy Park3 Author Orcid Image ;   David Wild3 Author Orcid Image ;   Babar Khan1, 4 Author Orcid Image ;   David A Haggstrom1, 4 Author Orcid Image ;   Shaun Grannis1, 5 Author Orcid Image
Article Authors Cited by (8) Tweetations (4) Metrics

Journals

  1. Rosario B, Zhang A, Patel M, Rajmane A, Xie N, Weeraratne D, Alterovitz G. Characterizing Thrombotic Complication Risk Factors Associated With COVID-19 via Heterogeneous Patient Data: Retrospective Observational Study. Journal of Medical Internet Research 2022;24(10):e35860 View
  2. Liu B, Zhang M, Li X, Liu L, Li Q, Liang Z, Xu L, Li L, Su Y, Chong K. Influence of epidemic situation on COVID-19 vaccination between urban and rural residents in China-Vietnam border area: A cross-sectional survey. PLOS ONE 2022;17(7):e0270345 View
  3. Lee M, Goh K, Koh D, Chong S, Chua R. The Telemedicine Demand Index and its Utility in Managing COVID-19 Case Surges. Telemedicine and e-Health 2024;30(2):545 View
  4. Berg T, Marino K, Kintziger K. The Application of Model-Based Systems Engineering to Rural Healthcare System Disaster Planning: A Scoping Review. International Journal of Disaster Risk Science 2023;14(3):357 View
  5. 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
  6. Borna S, Maniaci M, Haider C, Maita K, Torres-Guzman R, Avila F, Lunde J, Coffey J, Demaerschalk B, Forte A. Artificial Intelligence Models in Health Information Exchange: A Systematic Review of Clinical Implications. Healthcare 2023;11(18):2584 View
  7. Berg T, Kintziger K, Crumly J, Lawson S, Myers C, Stansberry T. Development of a Proof-of-Concept Multi-Method Computer Simulation to Support Rural Healthcare Disaster Preparedness Planning. International Journal of Disaster Risk Science 2024;15(3):346 View
  8. Beishuizen B, Stein M, Buis J, Tostmann A, Green C, Duggan J, Connolly M, Rovers C, Timen A. A systematic literature review on public health and healthcare resources for pandemic preparedness planning. BMC Public Health 2024;24(1) View