Published on in Vol 9, No 4 (2021): April
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/25884, first published
.
Journals
- Satu M, Howlader K, Mahmud M, Kaiser M, Shariful Islam S, Quinn J, Alyami S, Moni M. Short-Term Prediction of COVID-19 Cases Using Machine Learning Models. Applied Sciences 2021;11(9):4266 View
- Aktar S, Talukder A, Ahamad M, Kamal A, Khan J, Protikuzzaman M, Hossain N, Azad A, Quinn J, Summers M, Liaw T, Eapen V, Moni M. Machine Learning Approaches to Identify Patient Comorbidities and Symptoms That Increased Risk of Mortality in COVID-19. Diagnostics 2021;11(8):1383 View
- Yu Z, He L, Luo W, Tse R, Pau G. Deep Learning Hybrid Models for COVID-19 Prediction. Journal of Global Information Management 2022;30(10):1 View
- Matysek A, Studnicka A, Smith W, Hutny M, Gajewski P, Filipiak K, Goh J, Yang G. Influence of Co-morbidities During SARS-CoV-2 Infection in an Indian Population. Frontiers in Medicine 2022;9 View
- Ahamed K, Islam M, Uddin A, Akhter A, Paul B, Yousuf M, Uddin S, Quinn J, Moni M. A deep learning approach using effective preprocessing techniques to detect COVID-19 from chest CT-scan and X-ray images. Computers in Biology and Medicine 2021;139:105014 View
- Singh V, Kamaleswaran R, Chalfin D, Buño-Soto A, San Roman J, Rojas-Kenney E, Molinaro R, von Sengbusch S, Hodjat P, Comaniciu D, Kamen A. A deep learning approach for predicting severity of COVID-19 patients using a parsimonious set of laboratory markers. iScience 2021;24(12):103523 View
- Abdalrada A, Abawajy J, Al-Quraishi T, Islam S. Machine learning models for prediction of co-occurrence of diabetes and cardiovascular diseases: a retrospective cohort study. Journal of Diabetes & Metabolic Disorders 2022;21(1):251 View
- Ma R, Zheng X, Wang P, Liu H, Zhang C. The prediction and analysis of COVID-19 epidemic trend by combining LSTM and Markov method. Scientific Reports 2021;11(1) View
- Christakis N, Tirchas P, Politis M, Achladianakis M, Avgenikou E, Kossioris G. COVID-LIBERTY, A Machine Learning Computational Framework for the Study of the Covid-19 Pandemic in Europe. Part 2: Setting up the Framework with Ensemble Modeling. International Journal of Neural Networks and Advanced Applications 2021;8:27 View
- Hatmal M, Al-Hatamleh M, Olaimat A, Mohamud R, Fawaz M, Kateeb E, Alkhairy O, Tayyem R, Lounis M, Al-Raeei M, Dana R, Al-Ameer H, Taha M, Bindayna K. Reported Adverse Effects and Attitudes among Arab Populations Following COVID-19 Vaccination: A Large-Scale Multinational Study Implementing Machine Learning Tools in Predicting Post-Vaccination Adverse Effects Based on Predisposing Factors. Vaccines 2022;10(3):366 View
- Dairi A, Harrou F, Sun Y. Deep Generative Learning-Based 1-SVM Detectors for Unsupervised COVID-19 Infection Detection Using Blood Tests. IEEE Transactions on Instrumentation and Measurement 2022;71:1 View
- 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
- Liu X, Hasan M, Ahmed K, Hossain M. Machine learning to analyse omic-data for COVID-19 diagnosis and prognosis. BMC Bioinformatics 2023;24(1) View
- Alabbad D, Almuhaideb A, Alsunaidi S, Alqudaihi K, Alamoudi F, Alhobaishi M, Alaqeel N, Alshahrani M. Machine learning model for predicting the length of stay in the intensive care unit for Covid-19 patients in the eastern province of Saudi Arabia. Informatics in Medicine Unlocked 2022;30:100937 View
- Effah C, Miao R, Drokow E, Agboyibor C, Qiao R, Wu Y, Miao L, Wang Y. Machine learning-assisted prediction of pneumonia based on non-invasive measures. Frontiers in Public Health 2022;10 View
- Chowdhury U, Faruqe M, Mehedy M, Ahmad S, Islam M, Shoombuatong W, Azad A, Moni M. Effects of Bacille Calmette Guerin (BCG) vaccination during COVID-19 infection. Computers in Biology and Medicine 2021;138:104891 View
- Jung C, Mamandipoor B, Fjølner J, Bruno R, Wernly B, Artigas A, Bollen Pinto B, Schefold J, Wolff G, Kelm M, Beil M, Sviri S, van Heerden P, Szczeklik W, Czuczwar M, Elhadi M, Joannidis M, Oeyen S, Zafeiridis T, Marsh B, Andersen F, Moreno R, Cecconi M, Leaver S, De Lange D, Guidet B, Flaatten H, Osmani V. Disease-Course Adapting Machine Learning Prognostication Models in Elderly Patients Critically Ill With COVID-19: Multicenter Cohort Study With External Validation. JMIR Medical Informatics 2022;10(3):e32949 View
- Phuong J, Hyland S, Mooney S, Long D, Takeda K, Vavilala M, O’Hara K, Khubchandani J. Sociodemographic and clinical features predictive of SARS-CoV-2 test positivity across healthcare visit-types. PLOS ONE 2021;16(10):e0258339 View
- Saada H, Pagneux Q, Wei J, Live L, Roussel A, Dogliani A, Die Morini L, Engelmann I, Alidjinou E, Rolland A, Faure E, Poissy J, Labreuche J, Lee G, Li P, Curran G, Jawhari A, Yunda J, Melinte S, Legay A, Gala J, Devos D, Boukherroub R, Szunerits S. Sensing of COVID-19 spike protein in nasopharyngeal samples using a portable surface plasmon resonance diagnostic system. Sensors & Diagnostics 2022;1(5):1021 View
- Abayomi-Alli O, Damaševičius R, Maskeliūnas R, Misra S. An Ensemble Learning Model for COVID-19 Detection from Blood Test Samples. Sensors 2022;22(6):2224 View
- Araújo D, Veloso A, Borges K, Carvalho M. Prognosing the risk of COVID-19 death through a machine learning-based routine blood panel: A retrospective study in Brazil. International Journal of Medical Informatics 2022;165:104835 View
- Kwasniewski M, Korotko U, Chwialkowska K, Niemira M, Jaroszewicz J, Sobala-Szczygiel B, Puzanowska B, Moniuszko-Malinowska A, Pancewicz S, Parfieniuk-Kowerda A, Martonik D, Zarębska-Michaluk D, Simon K, Pazgan-Simon M, Mozer-Lisewska I, Bura M, Adamek A, Tomasiewicz K, Pawłowska M, Piekarska A, Berkan-Kawińska A, Horban A, Kowalska J, Podlasin R, Wasilewski P, Azzadin A, Czuczwar M, Borys M, Piwowarczyk P, Czaban S, Bogocz J, Ochab M, Kruk A, Uszok S, Bielska A, Szalkowska A, Raczkowska J, Sokolowska G, Chorostowska-Wynimko J, Jezela-Stanek A, Rozy A, Lechowicz U, Polowianiuk U, Tycinska A, Grubczak K, Starosz A, Izdebska W, Krzeminski T, Bousquet J, Sokolowska M, Franchini G, Hadlock J, Kretowski A, Eljaszewicz A, Flisiak R, Moniuszko M. Implementation of the User-Friendly Odds Ratio Calculator for Unvaccinated Individuals in a Country with a High COVID-19 Death Toll. SSRN Electronic Journal 2022 View
- Harrou F, Dairi A, Dorbane A, Kadri F, Sun Y. Semi-Supervised KPCA-Based Monitoring Techniques for Detecting COVID-19 Infection through Blood Tests. Diagnostics 2023;13(8):1466 View
- Rahman T, Chowdhury M, Khandakar A, Mahbub Z, Hossain M, Alhatou A, Abdalla E, Muthiyal S, Islam K, Kashem S, Khan M, Zughaier S, Hossain M. BIO-CXRNET: a robust multimodal stacking machine learning technique for mortality risk prediction of COVID-19 patients using chest X-ray images and clinical data. Neural Computing and Applications 2023;35(24):17461 View
- Khanna V, Chadaga K, Sampathila N, Prabhu S, P. R. A machine learning and explainable artificial intelligence triage-prediction system for COVID-19. Decision Analytics Journal 2023;7:100246 View
- Kessler R, Philipp J, Wilfer J, Kostev K. Predictive Attributes for Developing Long COVID—A Study Using Machine Learning and Real-World Data from Primary Care Physicians in Germany. Journal of Clinical Medicine 2023;12(10):3511 View
- Abbasi Habashi S, Koyuncu M, Alizadehsani R. A Survey of COVID-19 Diagnosis Using Routine Blood Tests with the Aid of Artificial Intelligence Techniques. Diagnostics 2023;13(10):1749 View
- Chadaga K, Prabhu S, Sampathila N, Chadaga R. Severity prediction in COVID-19 patients using clinical markers and explainable artificial intelligence: A stacked ensemble machine learning approach. Intelligent Decision Technologies 2023;17(4):959 View
- Pisano F, Cannas B, Fanni A, Pasella M, Canetto B, Giglio S, Mocci S, Chessa L, Perra A, Littera R. Decision trees for early prediction of inadequate immune response to coronavirus infections: a pilot study on COVID-19. Frontiers in Medicine 2023;10 View
- Al Shaqsi J, Borghan M, Drogham O, Al Whahaibi S. A machine learning approach to predict the parameters of COVID‐19 severity to improve the diagnosis protocol in Oman. SN Applied Sciences 2023;5(10) View
- Al Shaqsi J, Drogham O, Aburass S. Advanced machine learning based exploration for predicting pandemic fatality: Oman dataset. Informatics in Medicine Unlocked 2023;43:101393 View
- Uddin M, Ahamad M, Hoque M, Walid M, Aktar S, Alotaibi N, Alyami S, Kabir M, Moni M. A Comparison of Machine Learning Techniques for the Detection of Type-2 Diabetes Mellitus: Experiences from Bangladesh. Information 2023;14(7):376 View
- Farahat I, Aladrousy W, Elhoseny M, Tolba A, Elmougy S. CAD system for intelligent grading of COVID-19 severity with green computing and low carbon footprint analysis. Expert Systems with Applications 2023;234:121108 View
- Ghaderzadeh M, Asadi F, Ramezan Ghorbani N, Almasi S, Taami T. Toward artificial intelligence (AI) applications in the determination of COVID-19 infection severity: considering AI as a disease control strategy in future pandemics. Iranian Journal of Blood and Cancer 2023;15(3):93 View
- Tehrani S, Zarvani M, Amiri P, Ghods Z, Raoufi M, Safavi-Naini S, Soheili A, Gharib M, Abbasi H. Visual transformer and deep CNN prediction of high-risk COVID-19 infected patients using fusion of CT images and clinical data. BMC Medical Informatics and Decision Making 2023;23(1) View
- Hussain Z, Borah M, Ahmed R. Computational methods for studying relationship between nutritional status and respiratory viral diseases: a systematic review. Artificial Intelligence Review 2024;57(1) View
- Farahat I, Sharafeldeen A, Ghazal M, Alghamdi N, Mahmoud A, Connelly J, van Bogaert E, Zia H, Tahtouh T, Aladrousy W, Tolba A, Elmougy S, El-Baz A. An AI-based novel system for predicting respiratory support in COVID-19 patients through CT imaging analysis. Scientific Reports 2024;14(1) View
- Tutsoy O, Koç G. Deep self-supervised machine learning algorithms with a novel feature elimination and selection approaches for blood test-based multi-dimensional health risks classification. BMC Bioinformatics 2024;25(1) View
- Sagar D, Dwivedi T, Gupta A, Aggarwal P, Bhatnagar S, Mohan A, Kaur P, Gupta R. Clinical Features Predicting COVID-19 Severity Risk at the Time of Hospitalization. Cureus 2024 View
- Kim G, Ju C, Seok H, Lee D. Adaptive Stacking Ensemble Techniques for Early Severity Classification of COVID-19 Patients. Applied Sciences 2024;14(7):2715 View
- Debnath A, Tarafdar A, Reddy A, Bhattacharya P. ROVM integrated advanced machine learning-based malaria prediction strategy in Tripura. The Journal of Supercomputing 2024;80(11):15725 View
- Shaheen R, Akram B, Zafar A, Waheed T. Comparative Analysis of Supervised Machine Learning Algorithms for COVID-19 Prediction. Sir Syed University Research Journal of Engineering & Technology 2024;14(1):12 View
- Ortiz-Barrios M, Ishizaka A, Barbati M, Arias-Fonseca S, Khan J, Gul M, Yücesan M, Alfaro-Saíz J, Pérez-Aguilar A. Integrating discrete-event simulation and artificial intelligence for shortening bed waiting times in hospitalization departments during respiratory disease seasons. Computers & Industrial Engineering 2024;194:110405 View
- Araujo Gomes G, Beltrão F, Fragoso W, Lemos S. Discrimination between Covid-19 positive and negative blood serum based on excitation-emission matrix fluorescence spectroscopy and chemometrics. Talanta 2024;280:126788 View
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- Ahmed S, Islam S. The Science behind the COVID Pandemic and Healthcare Technology Solutions. View
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- Guest P, Abbasifard M, Jamialahmadi T, Majeed M, Kesharwani P, Sahebkar A. Multiplex Biomarker Techniques. View
- Qi X, Shen L, Chen J, Shi M, Shen B. Translational Informatics. View
- Adibi S, Rajabifard A, Islam S, Ahmadvand A. The Science behind the COVID Pandemic and Healthcare Technology Solutions. View
- Ikramov A, Anvarov K, Sharipova V, Iskhakov N, Abdurakhmonov A, Alimov A. AI 2021: Advances in Artificial Intelligence. View
- Ani R, Deepa O, Arundhathi M, Darsana J. Innovations in Computer Science and Engineering. View
- Devkar A, Kanade A. AI Technologies for Information Systems and Management Science. View