Enhancing advanced cervical cell categorization with cluster-based intelligent systems by a novel integrated CNN approach with skip mechanisms and GAN-based augmentation

Enhancing advanced cervical cell categorization with cluster-based intelligent systems by a novel integrated CNN approach with skip mechanisms and GAN-based augmentation

Abstract Cervical cancer is one of the biggest challenges in global health, thus it forms a critical need for early detection technologies that could improve patient prognosis and inform treatment decisions. This development in the form of an early detection mechanism increases the chances of succes...

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Bibliographic Details
Main Authors: Gunjan Shandilya, Sheifali Gupta, Ahmad Almogren, Salil Bharany, Ayman Altameem, Ateeq Ur Rehman, Seada Hussen
Format: Article
Language:English
Published: Nature Portfolio 2024-11-01
Series:Scientific Reports
Subjects:
Convolutional neural network (CNN)
Generative adversarial networks (GANs)
Skip connection
SipakMed dataset
Cervical cancer (CC)
Deep learning (DL)
Online Access:https://doi.org/10.1038/s41598-024-80260-1
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https://doi.org/10.1038/s41598-024-80260-1

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