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Updated: Jul 1, 2026

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data
09:47

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data

Published on: December 15, 2023

使用深度学习和基于XAI的可解释特征选择从血液基因表达数据中预测阿尔茨海默病

J Hariharan1, R Jothi2

  • 1School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, Vandalur-Kelambakkam Road, Chennai, Tamilnadu, 600127, India.

Scientific reports
|February 10, 2026
PubMed
概括

这项研究使用机器学习识别了用于早期阿尔茨海默病 (AD) 检测的关键血液基因生物标志物. 我们的方法显著提高了这种神经退行性疾病的诊断准确性和解释性.

关键词:
预测阿尔茨海默病的疾病预测.血液中的基因生物标志物深度学习是一种深度学习.深度神经网络是一个神经网络.可解释的人工智能功能选择 功能选择

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