Enhancing accessibility for improved diagnosis with modified EfficientNetV2-S and cyclic learning rate strategy in women with disabilities and breast cancer

Enhancing accessibility for improved diagnosis with modified EfficientNetV2-S and cyclic learning rate strategy in women with disabilities and breast cancer

Breast cancer, a prevalent cancer among women worldwide, necessitates precise and prompt detection for successful treatment. While conventional histopathological examination is the benchmark, it is a lengthy process and prone to variations among different observers. Employing machine learning to aut...

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Bibliographic Details
Main Authors: Moteeb Al Moteri, T. R. Mahesh, Arastu Thakur, V. Vinoth Kumar, Surbhi Bhatia Khan, Mohammed Alojail
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-03-01
Series:Frontiers in Medicine
Subjects:
machine learning
EfficientNetV2
histopathological image classification
deep learning
image processing
BreakHis dataset
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2024.1373244/full

Internet

https://www.frontiersin.org/articles/10.3389/fmed.2024.1373244/full

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