A Novel Ensemble-based Classifier for Detecting the COVID-19 Disease for Infected Patients
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DOI: 10.1007/s10796-021-10132-w
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References listed on IDEAS
- Patricia Baudier & Galina Kondrateva & Chantal Ammi & Victor Chang & Francesco Schiavone, 2021. "Patients’ perceptions of teleconsultation during COVID-19: a cross-national study," Post-Print hal-03052149, HAL.
- Baudier, Patricia & Kondrateva, Galina & Ammi, Chantal & Chang, Victor & Schiavone, Francesco, 2021. "Patients’ perceptions of teleconsultation during COVID-19: A cross-national study," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
- Abdel-Basset, Mohamed & Chang, Victor & Nabeeh, Nada A., 2021. "An intelligent framework using disruptive technologies for COVID-19 analysis," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
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- Victor Chang & Carole Goble & Muthu Ramachandran & Lazarus Jegatha Deborah & Reinhold Behringer, 2021. "Editorial on Machine Learning, AI and Big Data Methods and Findings for COVID-19," Information Systems Frontiers, Springer, vol. 23(6), pages 1363-1367, December.
- Abderrazek Azri & Cécile Favre & Nouria Harbi & Jérôme Darmont & Camille Noûs, 2023. "Rumor Classification through a Multimodal Fusion Framework and Ensemble Learning," Information Systems Frontiers, Springer, vol. 25(5), pages 1795-1810, October.
- Jyoti Choudrie & Shruti Patil & Ketan Kotecha & Nikhil Matta & Ilias Pappas, 2021. "Applying and Understanding an Advanced, Novel Deep Learning Approach: A Covid 19, Text Based, Emotions Analysis Study," Information Systems Frontiers, Springer, vol. 23(6), pages 1431-1465, December.
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Keywords
Machine learning; COVID-19; Artificial intelligence; Quality of service; Corona virus; Ensemble classifier;All these keywords.
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