Identifying underlying patterns in Alzheimer's disease trajectory: a deep learning approach and Mendelian randomization analysis-Reference-Cited by-同舟云学术

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Identifying underlying patterns in Alzheimer's disease trajectory: a deep learning approach and Mendelian randomization analysis

Published:2023-10 Issue: Volume:64 Page:102247
ISSN:2589-5370
Container-title:eClinicalMedicine
language:en
Short-container-title:eClinicalMedicine

Author:

Yi Fan^ORCID,Zhang Yaoyun,Yuan Jing,Liu Ziyue^ORCID,Zhai Feifei,Hao Ankai,Wu Fei,Somekh Judith,Peleg Mor^ORCID,Zhu Yi-Cheng,Huang Zhengxing^ORCID

Publisher

Elsevier BV

Subject

General Medicine

Reference62 articles.

1. Alzheimer disease;Apostolova;Continuum,2016

2. Advances in the early detection of Alzheimer's disease;Nestor;Nat Med,2004

3. Core candidate neurochemical and imaging biomarkers of Alzheimer's disease;Hampel;Alzheimers Dement,2008

4. Classification and basic pathology of Alzheimer disease;Duyckaerts;Acta Neuropathol,2009

5. Neuroimaging markers for the prediction and early diagnosis of Alzheimer's disease dementia;Ewers;Trends Neurosci,2011

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1. The Association Between Surgery and Mild Cognitive Impairment: Insight from a Case-Control Study;Journal of Alzheimer's Disease;2024-08-13

2. Feasibility study of ResNet‐50 in the distinction of intraoral neural tumors using histopathological images;Journal of Oral Pathology & Medicine;2024-06-04

3. Distance-based novelty detection model for identifying individuals at risk of developing Alzheimer's disease;Frontiers in Aging Neuroscience;2024-04-15

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