Convolutional neural network based data interpretable framework for Alzheimer’s treatment planning

Convolutional neural network based data interpretable framework for Alzheimer’s treatment planning

Abstract Alzheimer’s disease (AD) is a neurological disorder that predominantly affects the brain. In the coming years, it is expected to spread rapidly, with limited progress in diagnostic techniques. Various machine learning (ML) and artificial intelligence (AI) algorithms have been employed to de...

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Bibliographic Details
Main Authors: Sazia Parvin, Sonia Farhana Nimmy, Md Sarwar Kamal
Format: Article
Language:English
Published: SpringerOpen 2024-02-01
Series:Visual Computing for Industry, Biomedicine, and Art
Subjects:
Multimodal
Region-based convolutional neural network
Layer-wise relevance propagation
Submodular pick local interpretable model-agnostic explanations
Graphical genes tree
Alzheimer’s disease
Online Access:https://doi.org/10.1186/s42492-024-00154-x

Internet

https://doi.org/10.1186/s42492-024-00154-x

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