Deep Learning for Leukemia Classification: Performance Analysis and Challenges Across Multiple Architectures

Deep Learning for Leukemia Classification: Performance Analysis and Challenges Across Multiple Architectures

Leukemia is a very heterogeneous and complex blood cancer, which poses a significant challenge in its proper categorization and diagnosis. This paper aims to introduce various deep learning architectures, namely EfficientNet, LeNet, AlexNet, ResNet, VGG, and custom CNNs, for improved classification...

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Bibliographic Details
Main Authors: Hari Mohan Rai, B. Omkar Lakshmi Jagan, N. Thiruapthi Rao, Thayyaba Khatoon Mohammed, Neha Agarwal, Hanaa A. Abdallah, Saurabh Agarwal
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Fractal and Fractional
Subjects:
leukemia classification
deep learning architectures
medical image analysis
web-based diagnostic interface
Online Access:https://www.mdpi.com/2504-3110/9/6/337
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