Prediction and Feature Importance Analysis for Severity of COVID-19 in South Korea Using Artificial Intelligence: Model Development and Validation

Journals

1. Saleh M, AlHamaydeh M, Zakaria M. Shear capacity prediction for reinforced concrete deep beams with web openings using artificial intelligence methods. Engineering Structures 2023;280:115675 View
2. Gonçalves A, de Araujo G, Garcia L, Amaral F, Schneider I. Feature Importance Analysis by Nowcasting Perspective to Predict COVID-19. Mobile Networks and Applications 2022;27(5):1967 View
3. Neves da Silva L, Domingues Fernandes R, Costa R, Oliveira A, Sá A, Mosca A, Oliveira B, Braga M, Mendes M, Carvalho A, Moreira P, Santa Cruz A. Prediction of Noninvasive Ventilation Failure in COVID-19 Patients: When Shall We Stop?. Cureus 2022 View
4. Lau Y, Dulebenets M, Yip H, Tang Y. Healthcare Supply Chain Management under COVID-19 Settings: The Existing Practices in Hong Kong and the United States. Healthcare 2022;10(8):1549 View
5. Wong K, Xiang Y, Yin L, So H. Uncovering Clinical Risk Factors and Predicting Severe COVID-19 Cases Using UK Biobank Data: Machine Learning Approach. JMIR Public Health and Surveillance 2021;7(9):e29544 View
6. Doyle R. Machine Learning–Based Prediction of COVID-19 Mortality With Limited Attributes to Expedite Patient Prognosis and Triage: Retrospective Observational Study. JMIRx Med 2021;2(4):e29392 View
7. Altini N, Brunetti A, Mazzoleni S, Moncelli F, Zagaria I, Prencipe B, Lorusso E, Buonamico E, Carpagnano G, Bavaro D, Poliseno M, Saracino A, Schirinzi A, Laterza R, Di Serio F, D’Introno A, Pesce F, Bevilacqua V. Predictive Machine Learning Models and Survival Analysis for COVID-19 Prognosis Based on Hematochemical Parameters. Sensors 2021;21(24):8503 View
8. Tolmachev I, Kaverina I, Vrazhnov D, Starikov I, Starikova E, Kostuchenko E. Application of Artificial Intelligence Methods Depending on the Tasks Solved during COVID-19 Pandemic. COVID 2022;2(10):1341 View
9. Demko I, Korchagin E, Cherkashin O, Gordeeva N, Anikin D, Anikina D. Possibilities of information systems for prediction of outcomes of new coronavirus infection COVID-19. Meditsinskiy sovet = Medical Council 2022;(4):42 View
10. Chung H, Park C, Kang W, Lee J. Gender Bias in Artificial Intelligence: Severity Prediction at an Early Stage of COVID-19. Frontiers in Physiology 2021;12 View
11. 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
12. Paul S, Saha A, Biswas A, Zulfiker M, Arefin M, Rahman M, Reza A. Combating Covid-19 using machine learning and deep learning: Applications, challenges, and future perspectives. Array 2023;17:100271 View
13. Chowdhury N, Kabir M, Rahman M, Islam S. Machine learning for detecting COVID-19 from cough sounds: An ensemble-based MCDM method. Computers in Biology and Medicine 2022;145:105405 View
14. Ng A, Wei B, Jain J, Ward E, Tandon S, Moskowitz J, Krogh-Jespersen S, Wakschlag L, Alshurafa N. Predicting the Next-Day Perceived and Physiological Stress of Pregnant Women by Using Machine Learning and Explainability: Algorithm Development and Validation. JMIR mHealth and uHealth 2022;10(8):e33850 View
15. Hosseinzadeh Kasani P, Lee J, Park C, Yun C, Jang J, Lee S. Evaluation of nutritional status and clinical depression classification using an explainable machine learning method. Frontiers in Nutrition 2023;10 View

Books/Policy Documents

1. Badiola-Zabala G, Lopez-Guede J, Estevez J, Graña M. Hybrid Artificial Intelligent Systems. View