A deep learning model for Alzheimer's disease diagnosis based on patient clinical records.

Journal: Computers in biology and medicine
PMID: 38113682

Abstract

BACKGROUND: Dementia, with Alzheimer's disease (AD) being the most common type of this neurodegenerative disease, is an under-diagnosed health problem in older people. The creation of classification models based on AD risk factors using Deep Learning is a promising tool to minimize the impact of under-diagnosis.

Authors

  • J L Ávila-Jiménez
    Departament of Electronic and Computer Engineering. Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Cordoba, Córdoba, Spain.
  • Vanesa Cantón-Habas
    Maimonides Institute for Biomedical Research, Reina Sofia University Hospital, University of Córdoba, Spain. Electronic address: n92cahav@uco.es.
  • María Del Pilar Carrera-González
    Maimonides Institute for Biomedical Research, Reina Sofia University Hospital, University of Córdoba, Spain; Experimental and Clinical Physiopathology Research Group CTS-1039; Department of Health Sciences, Faculty of Health Sciences; University of Jaén, Campus Universitario Las Lagunillas, Jaén, Spain.
  • Manuel Rich-Ruiz
    Maimonides Institute for Biomedical Research, Reina Sofia University Hospital, University of Córdoba, Spain; CIBER on Fragility and Healthy Aging (CIBERFES), Madrid, Spain; Instituto de Salud Carlos III, Nursing and Healthcare Research Unit (Investén-isciii), Madrid, Spain.
  • Sebastián Ventura
    Department of Computer Science and Numerical Analysis, University of Córdoba Rabanales Campus, 14071 Córdoba, Spain.

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