Diagnosis of Alzheimer's disease and behavioural variant frontotemporal dementia with machine learning‐aided neuropsychological assessment using feature engineering and genetic algorithms-Reference-Cited by-同舟云学术

Diagnosis of Alzheimer's disease and behavioural variant frontotemporal dementia with machine learning‐aided neuropsychological assessment using feature engineering and genetic algorithms

Published:2022-01-11 Issue:2 Volume:37 Page:
ISSN:0885-6230
Container-title:International Journal of Geriatric Psychiatry
language:en
Short-container-title:Int J Geriat Psychiatry

Author:

Garcia‐Gutierrez Fernando¹²,Delgado‐Alvarez Alfonso¹,Delgado‐Alonso Cristina¹,Díaz‐Álvarez Josefa³,Pytel Vanesa¹,Valles‐Salgado Maria¹,Gil María Jose¹,Hernández‐Lorenzo Laura¹²,Matías‐Guiu Jorge¹,Ayala José L.²,Matias‐Guiu Jordi A.¹^ORCID

Affiliation:

1. Department of Neurology Hospital Clínico San Carlos San Carlos Research Health Institute (IdISSC) Universidad Complutense Madrid Spain

2. Department of Computer Architecture and Automation Universidad Complutense Madrid Spain

3. Department of Computer Architecture and Communications Centro Universitario de Mérida Universidad de Extremadura Merida Spain

Funder

European Regional Development Fund

Junta de Extremadura

Spanish Ministry of Science and Innovation

Ministerio de Economía y Competitividad

Instituto de Salud Carlos III

Publisher

Wiley

Subject

Psychiatry and Mental health,Geriatrics and Gerontology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/gps.5667

Reference50 articles.

1. Clinical Neurology and Epidemiology of the Major Neurodegenerative Diseases

2. A clinicopathological approach to the diagnosis of dementia

3. Timely Diagnosis for Alzheimer’s Disease: A Literature Review on Benefits and Challenges

4. Alzheimer Disease: An Update on Pathobiology and Treatment Strategies

5. Neuropsychology of Alzheimer's Disease

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