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

Artificial Intelligence (1198) Clinical Information and Decision Making (1328) JMIR Theme Issue: COVID-19 Special Issue (2391) Decision Support for Health Professionals (1137) Machine Learning (1385) Theme Issue: Medical Informatics and COVID-19 (103) Infectious Diseases (non-STD/STI) (1485) Outbreak and Pandemic Preparedness and Management (1675)

Published on in Vol 22, No 12 (2020): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25442, first published .
An Artificial Intelligence Model to Predict the Mortality of COVID-19 Patients at Hospital Admission Time Using Routine Blood Samples: Development and Validation of an Ensemble Model

An Artificial Intelligence Model to Predict the Mortality of COVID-19 Patients at Hospital Admission Time Using Routine Blood Samples: Development and Validation of an Ensemble Model

An Artificial Intelligence Model to Predict the Mortality of COVID-19 Patients at Hospital Admission Time Using Routine Blood Samples: Development and Validation of an Ensemble Model

Authors of this article:

Hoon Ko1 Author Orcid Image ;   Heewon Chung1 Author Orcid Image ;   Wu Seong Kang2 Author Orcid Image ;   Chul Park3 Author Orcid Image ;   Do Wan Kim4 Author Orcid Image ;   Seong Eun Kim5 Author Orcid Image ;   Chi Ryang Chung6 Author Orcid Image ;   Ryoung Eun Ko6 Author Orcid Image ;   Hooseok Lee1 Author Orcid Image ;   Jae Ho Seo7 Author Orcid Image ;   Tae-Young Choi8 Author Orcid Image ;   Rafael Jaimes9 Author Orcid Image ;   Kyung Won Kim10 Author Orcid Image ;   Jinseok Lee1 Author Orcid Image
Article Authors Cited by (59) Tweetations (10) Metrics

Journals

  1. di Filippo L, Doga M, Frara S, Giustina A. Hypocalcemia in COVID-19: Prevalence, clinical significance and therapeutic implications. Reviews in Endocrine and Metabolic Disorders 2022;23(2):299 View
  2. Lippi G, Henry B, Favaloro E. Mean Platelet Volume Predicts Severe COVID-19 Illness. Seminars in Thrombosis and Hemostasis 2021;47(04):456 View
  3. Khan I, Aslam N, Aljabri M, Aljameel S, Kamaleldin M, Alshamrani F, Chrouf S. Computational Intelligence-Based Model for Mortality Rate Prediction in COVID-19 Patients. International Journal of Environmental Research and Public Health 2021;18(12):6429 View
  4. Lin J, Chien T, Wang L, Chou W. An artificial neural network model to predict the mortality of COVID-19 patients using routine blood samples at the time of hospital admission. Medicine 2021;100(28):e26532 View
  5. Marcolino M, Pires M, Ramos L, Silva R, Oliveira L, Carvalho R, Mourato R, Sánchez-Montalvá A, Raventós B, Anschau F, Chatkin J, Nogueira M, Guimarães-Júnior M, Vietta G, Duani H, Ponce D, Ziegelmann P, Castro L, Ruschel K, Cimini C, Francisco S, Floriani M, Nascimento G, Farace B, Monteiro L, Souza-Silva M, Sales T, Martins K, Borges do Nascimento I, Fereguetti T, Ferrara D, Botoni F, Etges A, Schwarzbold A, Maurílio A, Scotton A, Weber A, Costa A, Glaeser A, Madureira A, Bhering A, de Castro B, da Silva C, Ramos C, Gomes C, de Carvalho C, Silveira D, Cezar E, Pereira E, Kroger E, Vallt F, Lucas F, Aranha F, Bartolazzi F, Crestani G, Bastos G, Madeira G, Noal H, Vianna H, Guimarães H, Gomes I, Molina I, Batista J, de Alvarenga J, Guimarães J, de Morais J, Rugolo J, Pontes K, dos Santos K, de Oliveira L, Pinheiro L, Pacheco L, Sousa L, Couto L, Kopittke L, de Moura L, Santos L, Cabral M, Souza M, Tofani M, Carneiro M, Ferreira M, Bicalho M, Lima M, Godoy M, Cardoso M, Figueiredo M, Sampaio N, Rangel N, Crespo N, de Oliveira N, Assaf P, Martelli P, Almeida R, Martins R, Lutkmeier R, Valacio R, Finger R, Cardoso R, Pozza R, Campos R, Menezes R, de Abreu R, Silva R, Guimarães S, Araújo S, Pereira S, Oliveira T, Kurtz T, de Oliveira T, Araújo T, Diniz T, dos Santos V, Gomes V, do Vale V, Ramires Y, Boersma E, Polanczyk C. ABC2-SPH risk score for in-hospital mortality in COVID-19 patients: development, external validation and comparison with other available scores. International Journal of Infectious Diseases 2021;110:281 View
  6. 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 J, Klee E, Salama M, Kipp B, Morice W, Jenkinson G. COVID-19 Mortality Prediction From Deep Learning in a Large Multistate Electronic Health Record and Laboratory Information System Data Set: Algorithm Development and Validation. Journal of Medical Internet Research 2021;23(9):e30157 View
  7. Ovcharenko E, Kutikhin A, Gruzdeva O, Kuzmina A, Slesareva T, Brusina E, Kudasheva S, Bondarenko T, Kuzmenko S, Osyaev N, Ivannikova N, Vavin G, Moses V, Danilov V, Komossky E, Klyshnikov K. Cardiovascular and Renal Comorbidities Included into Neural Networks Predict the Outcome in COVID-19 Patients Admitted to an Intensive Care Unit: Three-Center, Cross-Validation, Age- and Sex-Matched Study. Journal of Cardiovascular Development and Disease 2023;10(2):39 View
  8. Cheng J, Sollee J, Hsieh C, Yue H, Vandal N, Shanahan J, Choi J, Tran T, Halsey K, Iheanacho F, Warren J, Ahmed A, Eickhoff C, Feldman M, Mortani Barbosa E, Kamel I, Lin C, Yi T, Healey T, Zhang P, Wu J, Atalay M, Bai H, Jiao Z, Wang J. COVID-19 mortality prediction in the intensive care unit with deep learning based on longitudinal chest X-rays and clinical data. European Radiology 2022;32(7):4446 View
  9. Arora G, Joshi J, Mandal R, Shrivastava N, Virmani R, Sethi T. Artificial Intelligence in Surveillance, Diagnosis, Drug Discovery and Vaccine Development against COVID-19. Pathogens 2021;10(8):1048 View
  10. Mr. Sharan L. Pais , Rakshitha R , Rashmi S K , Ravish , Sathwik U Shetty . Robotics and Artificial Intelligence in Healthcare During COVID-19 Pandemic. International Journal of Advanced Research in Science, Communication and Technology 2022:349 View
  11. Yang D, Martinez C, Visuña L, Khandhar H, Bhatt C, Carretero J. Detection and analysis of COVID-19 in medical images using deep learning techniques. Scientific Reports 2021;11(1) View
  12. Roland T, Böck C, Tschoellitsch T, Maletzky A, Hochreiter S, Meier J, Klambauer G. Domain Shifts in Machine Learning Based Covid-19 Diagnosis From Blood Tests. Journal of Medical Systems 2022;46(5) View
  13. 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
  14. Guleria P, Ahmed S, Alhumam A, Srinivasu P. Empirical Study on Classifiers for Earlier Prediction of COVID-19 Infection Cure and Death Rate in the Indian States. Healthcare 2022;10(1):85 View
  15. Abegaz K, Etikan İ. Artificial Intelligence-Driven Ensemble Model for Predicting Mortality Due to COVID-19 in East Africa. Diagnostics 2022;12(11):2861 View
  16. Barough S, Safavi-Naini S, Siavoshi F, Tamimi A, Ilkhani S, Akbari S, Ezzati S, Hatamabadi H, Pourhoseingholi M. Generalizable machine learning approach for COVID-19 mortality risk prediction using on-admission clinical and laboratory features. Scientific Reports 2023;13(1) View
  17. Daniels S, Wei H, van Tongeren M, Denning D. Are platelet volume indices of clinical use in COVID-19? A systematic review. Frontiers in Cardiovascular Medicine 2022;9 View
  18. Shanbehzadeh M, Nopour R, Kazemi-Arpanahi H. Design of an artificial neural network to predict mortality among COVID-19 patients. Informatics in Medicine Unlocked 2022;31:100983 View
  19. Bartoszko J, Dranitsaris G, Wilcox M, Del Sorbo L, Mehta S, Peer M, Parotto M, Bogoch I, Riazi S. Development of a repeated-measures predictive model and clinical risk score for mortality in ventilated COVID-19 patients. Canadian Journal of Anesthesia/Journal canadien d'anesthésie 2022;69(3):343 View
  20. Bottino F, Tagliente E, Pasquini L, Napoli A, Lucignani M, Figà-Talamanca L, Napolitano A. COVID Mortality Prediction with Machine Learning Methods: A Systematic Review and Critical Appraisal. Journal of Personalized Medicine 2021;11(9):893 View
  21. Sarker S, Jamal L, Ahmed S, Irtisam N. Robotics and artificial intelligence in healthcare during COVID-19 pandemic: A systematic review. Robotics and Autonomous Systems 2021;146:103902 View
  22. Gupta V, Jain N, Sachdeva J, Gupta M, Mohan S, Bajuri M, Ahmadian A. Improved COVID-19 detection with chest x-ray images using deep learning. Multimedia Tools and Applications 2022;81(26):37657 View
  23. Mahmoodpoor A, Imani F, Soleimanpour H. COVID-19 Is Not Over and Needs Prediction Scores: An Endless Road!. Anesthesiology and Pain Medicine 2021;11(6) View
  24. Chen X, Cheng G, Wang F, Tao X, Xie H, Xu L. Machine and cognitive intelligence for human health: systematic review. Brain Informatics 2022;9(1) View
  25. Douthit B, Walden R, Cato K, Coviak C, Cruz C, D'Agostino F, Forbes T, Gao G, Kapetanovic T, Lee M, Pruinelli L, Schultz M, Wieben A, Jeffery A. Data Science Trends Relevant to Nursing Practice: A Rapid Review of the 2020 Literature. Applied Clinical Informatics 2022;13(01):161 View
  26. Meng Z, Guo S, Zhou Y, Li M, Wang M, Ying B. Applications of laboratory findings in the prevention, diagnosis, treatment, and monitoring of COVID-19. Signal Transduction and Targeted Therapy 2021;6(1) View
  27. 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
  28. Peng H, Hu C, Deng W, Huang L, Zhang Y, Luo B, Wang X, Long X, Huang X. Incubation period, clinical and lung CT features for early prediction of COVID-19 deterioration: development and internal verification of a risk model. BMC Pulmonary Medicine 2022;22(1) View
  29. Yacob Y, Alquran H, Mustafa W, Alsalatie M, Sakim H, Lola M. H. pylori Related Atrophic Gastritis Detection Using Enhanced Convolution Neural Network (CNN) Learner. Diagnostics 2023;13(3):336 View
  30. Monday H, Li J, Nneji G, Nahar S, Hossin M, Jackson J, Ejiyi C. COVID-19 Diagnosis from Chest X-ray Images Using a Robust Multi-Resolution Analysis Siamese Neural Network with Super-Resolution Convolutional Neural Network. Diagnostics 2022;12(3):741 View
  31. Rai N, Kaushik N, Kumar D, Raj C, Ali A. Mortality prediction of COVID-19 patients using soft voting classifier. International Journal of Cognitive Computing in Engineering 2022;3:172 View
  32. Han W, Han X, Zhou S, Zhu Q. The Development History and Research Tendency of Medical Informatics: Topic Evolution Analysis. JMIR Medical Informatics 2022;10(1):e31918 View
  33. Yadav A, Kumar V, Joshi D, Rajput D, Mishra H, Paruti B. Hybrid Artificial Intelligence-Based Models for Prediction of Death Rate in India Due to COVID-19 Transmission. International Journal of Reliable and Quality E-Healthcare 2023;12(2):1 View
  34. Liu C, Yao Z, Liu P, Tu Y, Chen H, Cheng H, Xie L, Xiao K. Early prediction of MODS interventions in the intensive care unit using machine learning. Journal of Big Data 2023;10(1) View
  35. Yen P, Chien T, Chou W, Tsai K. Using the Alluvial diagram to display variable characteristics for COVID-19 patients and research achievements on the topic of COVID-19, epidemiology, pathogenesis, and vaccine (CEPV): Bibliometric analysis. Medicine 2023;102(25):e33873 View
  36. Wang Y, Wang Z, Liu Y, Yu Q, Liu Y, Luo C, Wang S, Liu H, Liu M, Zhang G, Fan Y, Li K, Huang L, Duan M, Zhou F. Reconstructing the cytokine view for the multi-view prediction of COVID-19 mortality. BMC Infectious Diseases 2023;23(1) View
  37. Verzellesi L, Botti A, Bertolini M, Trojani V, Carlini G, Nitrosi A, Monelli F, Besutti G, Castellani G, Remondini D, Milanese G, Croci S, Sverzellati N, Salvarani C, Iori M. Machine and Deep Learning Algorithms for COVID-19 Mortality Prediction Using Clinical and Radiomic Features. Electronics 2023;12(18):3878 View
  38. Ha S, Choi S, Lee S, Wijaya R, Kim J, Joo E, Kim J. Predicting the Risk of Sleep Disorders Using a Machine Learning–Based Simple Questionnaire: Development and Validation Study. Journal of Medical Internet Research 2023;25:e46520 View
  39. Xin Y, Li H, Zhou Y, Yang Q, Mu W, Xiao H, Zhuo Z, Liu H, Wang H, Qu X, Wang C, Liu H, Yu K. The accuracy of artificial intelligence in predicting COVID-19 patient mortality: a systematic review and meta-analysis. BMC Medical Informatics and Decision Making 2023;23(1) View
  40. Giuste F, He L, Lais P, Shi W, Zhu Y, Hornback A, Tsai C, Isgut M, Anderson B, Wang M. Early and fair COVID-19 outcome risk assessment using robust feature selection. Scientific Reports 2023;13(1) View
  41. Li Z, Wang B, Liang H, Li Y, Zhang Z, Han L. A three-stage eccDNA based molecular profiling significantly improves the identification, prognosis assessment and recurrence prediction accuracy in patients with glioma. Cancer Letters 2023;574:216369 View
  42. Rajkumar E, Nguyen K, Radic S, Paa J, Geng Q. Machine Learning and Causal Approaches to Predict Readmissions and Its Economic Consequences Among Canadian Patients With Heart Disease: Retrospective Study. JMIR Formative Research 2023;7:e41725 View
  43. 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
  44. Kim J, Choi Y, Lee Y, Yeo S, Kim K, Kim M, Rahmati M, Yon D, Lee J. Limitations of the Cough Sound-Based COVID-19 Diagnosis Artificial Intelligence Model and its Future Direction: Longitudinal Observation Study. Journal of Medical Internet Research 2024;26:e51640 View
  45. Badiola-Zabala G, Lopez-Guede J, Estevez J, Graña M. Machine Learning First Response to COVID-19: A Systematic Literature Review of Clinical Decision Assistance Approaches during Pandemic Years from 2020 to 2022. Electronics 2024;13(6):1005 View
  46. Singh K, Kaur N, Prabhu A. Combating COVID-19 Crisis using Artificial Intelligence (AI) Based Approach: Systematic Review. Current Topics in Medicinal Chemistry 2024;24(8):737 View
  47. 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
  48. Hussain S, Songhua X, Aslam M, Hussain F, Ali I. Optimal Prognostic Accuracy: Machine Learning Approaches for COVID-19 Prognosis with Biomarkers and Demographic Information. New Generation Computing 2024 View
  49. Xie H, Jia Y, Liu S. Integration of artificial intelligence in clinical laboratory medicine: Advancements and challenges. Interdisciplinary Medicine 2024 View

Books/Policy Documents

  1. Sharma V, Dastidar M, Sutradhar S, Raj V, De Silva K, Roy S. COVID-19 and the Sustainable Development Goals. View
  2. Modegh R, Salimi A, Ilami S, Dehqan A, Dashti H, Javanmard S, Ghanaati H, Rabiee H. The Science behind the COVID Pandemic and Healthcare Technology Solutions. View
  3. Tintín V, Florez H. Computational Science and Its Applications – ICCSA 2021. View
  4. Davids J, Ashrafian H. Artificial Intelligence in Medicine. View
  5. Mena-Camilo E, Hernández-Nava G, Leyva-López S, Salazar-Colores S. XLVI Mexican Conference on Biomedical Engineering. View