2023
DOI: 10.32604/cmc.2023.031969
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A Hybrid Deep Fused Learning Approach to Segregate Infectious Diseases

Abstract: Humankind is facing another deadliest pandemic of all times in history, caused by COVID-19. Apart from this challenging pandemic, World Health Organization (WHO) considers tuberculosis (TB) as a preeminent infectious disease due to its high infection rate. Generally, both TB and COVID-19 severely affect the lungs, thus hardening the job of medical practitioners who can often misidentify these diseases in the current situation. Therefore, the time of need calls for an immediate and meticulous automatic diagnost… Show more

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Cited by 8 publications
(1 citation statement)
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“…In addition to image-based diagnostics, researchers have investigated other modalities for COVID-19 detection. In [44], the authors propose a hybrid deep-fused learning approach to segregate infectious diseases, including COVID-19. Their study explores the combination of multiple data modalities to improve the accuracy of disease segregation.…”
Section: Background and Related Workmentioning
confidence: 99%
“…In addition to image-based diagnostics, researchers have investigated other modalities for COVID-19 detection. In [44], the authors propose a hybrid deep-fused learning approach to segregate infectious diseases, including COVID-19. Their study explores the combination of multiple data modalities to improve the accuracy of disease segregation.…”
Section: Background and Related Workmentioning
confidence: 99%