NSGA-II-DL: Metaheuristic Optimal Feature Selection With Deep Learning Framework for HER2 Classification in Breast Cancer

NSGA-II-DL: Metaheuristic Optimal Feature Selection With Deep Learning Framework for HER2 Classification in Breast Cancer

Immunohistochemistry (IHC) slides are graded for breast cancer based on visual markers and morphological characteristics of stained membrane regions. The usage of whole slide images (WSIs) from histology in digital pathology algorithms for computer-assisted evaluations has increased recently. Human...

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Bibliographic Details
Main Authors: Tarik Ahmed Rashid, Jafar Majidpour, Rajermani Thinakaran, Malathy Batumalay, Deshinta Arrova Dewi, Bryar A. Hassan, Habibollah Dadgar, Hossein Arabi
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
HER2
CNN
transfer learning
NSGA-II optimizer
FlLpF
Online Access:https://ieeexplore.ieee.org/document/10463051/

Internet

https://ieeexplore.ieee.org/document/10463051/

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