ALL-Net: integrating CNN and explainable-AI for enhanced diagnosis and interpretation of acute lymphoblastic leukemia

ALL-Net: integrating CNN and explainable-AI for enhanced diagnosis and interpretation of acute lymphoblastic leukemia

This article presents a new model, ALL-Net, for the detection of acute lymphoblastic leukemia (ALL) using a custom convolutional neural network (CNN) architecture and explainable Artificial Intelligence (XAI). A dataset consisting of 3,256 peripheral blood smear (PBS) images belonging to four classe...

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Bibliographic Details
Main Authors: Abhiram Thiriveedhi, Swetha Ghanta, Sujit Biswas, Ashok K. Pradhan
Format: Article
Language:English
Published: PeerJ Inc. 2025-01-01
Series:PeerJ Computer Science
Subjects:
Acute lymphoblastic leukemia
Peripheral blood smear images
Convolutional neural networks
Explainable AI
Data augmentation
Online Access:https://peerj.com/articles/cs-2600.pdf
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