Published on in Vol 22, No 8 (2020): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/20259, first published .
Prognostic Modeling of COVID-19 Using Artificial Intelligence in the United Kingdom: Model Development and Validation

Prognostic Modeling of COVID-19 Using Artificial Intelligence in the United Kingdom: Model Development and Validation

Prognostic Modeling of COVID-19 Using Artificial Intelligence in the United Kingdom: Model Development and Validation

Journals

  1. Abdulaal A, Patel A, Charani E, Denny S, Alqahtani S, Davies G, Mughal N, Moore L. Comparison of deep learning with regression analysis in creating predictive models for SARS-CoV-2 outcomes. BMC Medical Informatics and Decision Making 2020;20(1) View
  2. Lorencin I, Baressi Šegota S, Anđelić N, Blagojević A, Šušteršić T, Protić A, Arsenijević M, Ćabov T, Filipović N, Car Z. Automatic Evaluation of the Lung Condition of COVID-19 Patients Using X-ray Images and Convolutional Neural Networks. Journal of Personalized Medicine 2021;11(1):28 View
  3. Pan P, Li Y, Xiao Y, Han B, Su L, Su M, Li Y, Zhang S, Jiang D, Chen X, Zhou F, Ma L, Bao P, Xie L. Prognostic Assessment of COVID-19 in the Intensive Care Unit by Machine Learning Methods: Model Development and Validation. Journal of Medical Internet Research 2020;22(11):e23128 View
  4. Ponsford M, Burton R, Smith L, Khan P, Andrews R, Cuff S, Tan L, Eberl M, Humphreys I, Babolhavaeji F, Artemiou A, Pandey M, Jolles S, Underwood J. Examining the utility of extended laboratory panel testing in the emergency department for risk stratification of patients with COVID-19: a single-centre retrospective service evaluation. Journal of Clinical Pathology 2021:jclinpath-2020-207157 View
  5. Jimenez-Solem E, Petersen T, Hansen C, Hansen C, Lioma C, Igel C, Boomsma W, Krause O, Lorenzen S, Selvan R, Petersen J, Nyeland M, Ankarfeldt M, Virenfeldt G, Winther-Jensen M, Linneberg A, Ghazi M, Detlefsen N, Lauritzen A, Smith A, de Bruijne M, Ibragimov B, Petersen J, Lillholm M, Middleton J, Mogensen S, Thorsen-Meyer H, Perner A, Helleberg M, Kaas-Hansen B, Bonde M, Bonde A, Pai A, Nielsen M, Sillesen M. Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients. Scientific Reports 2021;11(1) View
  6. Manco L, Maffei N, Strolin S, Vichi S, Bottazzi L, Strigari L. Basic of machine learning and deep learning in imaging for medical physicists. Physica Medica 2021;83:194 View
  7. Kwon Y, Toussie D, Finkelstein M, Cedillo M, Maron S, Manna S, Voutsinas N, Eber C, Jacobi A, Bernheim A, Gupta Y, Chung M, Fayad Z, Glicksberg B, Oermann E, Costa A. Combining Initial Radiographs and Clinical Variables Improves Deep Learning Prognostication in Patients with COVID-19 from the Emergency Department. Radiology: Artificial Intelligence 2021;3(2):e200098 View
  8. Chee M, Ong M, Siddiqui F, Zhang Z, Lim S, Ho A, Liu N. Artificial Intelligence Applications for COVID-19 in Intensive Care and Emergency Settings: A Systematic Review. International Journal of Environmental Research and Public Health 2021;18(9):4749 View
  9. 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
  10. 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
  11. Lan L, Sun W, Xu D, Yu M, Xiao F, Hu H, Xu H, Wang X. Artificial intelligence-based approaches for COVID-19 patient management. Intelligent Medicine 2021;1(1):10 View
  12. Abdulaal A, Patel A, Al-Hindawi A, Charani E, Alqahtani S, Davies G, Mughal N, Moore L. Clinical Utility and Functionality of an Artificial Intelligence–Based App to Predict Mortality in COVID-19: Mixed Methods Analysis. JMIR Formative Research 2021;5(7):e27992 View
  13. Snider B, McBean E, Yawney J, Gadsden S, Patel B. Identification of Variable Importance for Predictions of Mortality From COVID-19 Using AI Models for Ontario, Canada. Frontiers in Public Health 2021;9 View
  14. Stachel A, Keegan L, Blumberg S. Modeling transmission of pathogens in healthcare settings. Current Opinion in Infectious Diseases 2021;Publish Ahead of Print View
  15. Leite M, de Loiola Costa L, Cunha V, Kreniski V, de Oliveira Braga Filho M, da Cunha N, Costa F. Artificial intelligence and the future of life sciences. Drug Discovery Today 2021 View
  16. Galanter W, Rodríguez-Fernández J, Chow K, Harford S, Kochendorfer K, Pishgar M, Theis J, Zulueta J, Darabi H. Predicting clinical outcomes among hospitalized COVID-19 patients using both local and published models. BMC Medical Informatics and Decision Making 2021;21(1) View
  17. Khozeimeh F, Sharifrazi D, Izadi N, Joloudari J, Shoeibi A, Alizadehsani R, Gorriz J, Hussain S, Sani Z, Moosaei H, Khosravi A, Nahavandi S, Islam S. Combining a convolutional neural network with autoencoders to predict the survival chance of COVID-19 patients. Scientific Reports 2021;11(1) View
  18. Sankaranarayanan S, Balan J, Walsh J, Wu Y, Minnich S, Piazza A, Osborne C, Oliver G, Lesko J, Bates K, Khezeli K, Block D, DiGuardo M, Kreuter J, O’Horo J, Kalantari I, Klee E, Salama M, Kipp B, Morice II W, Jenkinson G. COVID-19 mortality prediction from deep learning in a large multistate EHR and LIS dataset: algorithm development and validation (Preprint). Journal of Medical Internet Research 2021 View

Books/Policy Documents

  1. Chiari M, Gerevini A, Olivato M, Putelli L, Rossetti N, Serina I. Artificial Intelligence in Medicine. View