Adaptive Mish activation and ranger optimizer-based SEA-ResNet50 model with explainable AI for multiclass classification of COVID-19 chest X-ray images

Adaptive Mish activation and ranger optimizer-based SEA-ResNet50 model with explainable AI for multiclass classification of COVID-19 chest X-ray images

Abstract A recent global health crisis, COVID-19 is a significant global health crisis that has profoundly affected lifestyles. The detection of such diseases from similar thoracic anomalies using medical images is a challenging task. Thus, the requirement of an end-to-end automated system is vastly...

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Bibliographic Details
Main Authors: S. R. Sannasi Chakravarthy, N. Bharanidharan, C. Vinothini, Venkatesan Vinoth Kumar, T. R. Mahesh, Suresh Guluwadi
Format: Article
Language:English
Published: BMC 2024-08-01
Series:BMC Medical Imaging
Subjects:
X-ray
COVID-19
Transfer learning
Explainable artificial intelligence
Deep-learning
Attention mechanism
Online Access:https://doi.org/10.1186/s12880-024-01394-2

Internet

https://doi.org/10.1186/s12880-024-01394-2

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