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Hybrid Attention Capsule Network for the Detection of Alzheimer's Disease-Associated Gene Expression Profiles
编号：12 访问权限：仅限参会人 更新：2026-07-28 21:49:17 浏览：25次 Online

报告开始：2026年07月30日 11:55（Asia/Kolkata）

报告时间：15min

所在会场：[S4] Computer Vision and Pattern Recognition [S4-1] Computer Vision and Pattern Recognition

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摘要
The goal of gene signature analysis in gene expression data is to correlate variations in the degree of expression of certain genes with the presence or absence of specific gene expressions. However, there are challenges because microarray databases are high dimensional and the sample count is limited. The study aims to investigate deep learning (DL) techniques, particularly neural networks, to predict Alzheimer's disease using gene expression data. First, the input gene expression data is pre-processed employing Z-score normalization and Missing value imputation methods. The most effective characteristics are then selected using the Chebyshev Pufferfish Algorithm (CPA), which reduces dimensionality. The proposed model introduces a novel Depthwise Separable Convolutional Attention-based Chi-Squared Capsule Network (DSCA-CSCN) for analyzing AD gene expressions using gene expression data. The proposed framework presents an integrated architecture that combines several effective techniques to enable simultaneous enhancement of gene expression discrimination and reduction of computational complexity in high-dimensional gene expression data. Furthermore, the Explainable AI method (XAI) analyzes the interactions between various attributes that can be conveniently captured and displayed using SHapley Additive Explanations (SHAP). The proposed framework attains accuracy (98%), precision (97.41%), recall (97.75%), f1-score (96.17%) and specificity (97.25%).
关键词
Gene Expression Data,Alzheimer;s disease,pre-processing,Chebyshev Pufferfish Algorithm (CPA),Depthwise Separable Convolutional Attention based Chi-Squared Capsule Network (DSCA-CSCN),SHapley Additive exPlanations (SHAP)
报告人
Remyamol K.M
- Cochin University of Science and Technology

稿件作者
Remyamol K.M Cochin University of Science and Technology
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重要日期

  • 会议日期

    07月30日

    2026

    至

    08月01日

    2026

  • 07月28日 2026

    注册截止日期

  • 07月30日 2026

    初稿截稿日期

主办单位
The United Societies of Science
承办单位
Kongunadu College of Engineering and Technology
协办单位
IEEE Section
IEEE Madras Section
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