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Data mining techniques applied in the neuropsychology domain: A systematic review

  • David Cordero
  • , Luis Miguel Alvear
  • , Marcos Orellana
  • , Maria Ines Acosta
  • , Alexandra Bueno
  • , Juan Fernando Lima
  • , Andres Patino
  • , Priscila Cedillo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The vast amount of data collected in the health care field allows researchers to apply different data mining techniques that may support and improve patients' condition. The neurocognitive field represents a new area of interest in which data mining techniques could be extremely useful to diagnose and treat impairments. This systematic literature review aims to identify the most relevant data mining techniques, tools, and approaches to collect, process, and represent results used in neuropsychology for the analysis of memory and cognitive attention. The results will contribute to the development of new tools to evaluate the neuropsychological variables cited before in elderly people in the context of a normal aging process.

Original languageEnglish
Title of host publicationProceedings - 2020 International Conference of Digital Transformation and Innovation Technology, INCODTRIN 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages89-96
Number of pages8
ISBN (Electronic)9781665423199
DOIs
StatePublished - Oct 2020
Externally publishedYes
Event1st International Conference of Digital Transformation and Innovation Technology, INCODTRIN 2020 - Quito, Ecuador
Duration: 28 Oct 202030 Oct 2020

Publication series

NameProceedings - 2020 International Conference of Digital Transformation and Innovation Technology, INCODTRIN 2020

Conference

Conference1st International Conference of Digital Transformation and Innovation Technology, INCODTRIN 2020
Country/TerritoryEcuador
CityQuito
Period28/10/2030/10/20

Keywords

  • Attention
  • Data Mining
  • Memory
  • Neuropsychology

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