Data Mining Algorithms and Techniques in Mental Health: A Systematic Review

Journal of Medical Systems
Susel Góngora AlonsoManuel Franco

Abstract

Data Mining in medicine is an emerging field of great importance to provide a prognosis and deeper understanding of disease classification, specifically in Mental Health areas. The main objective of this paper is to present a review of the existing research works in the literature, referring to the techniques and algorithms of Data Mining in Mental Health, specifically in the most prevalent diseases such as: Dementia, Alzheimer, Schizophrenia and Depression. Academic databases that were used to perform the searches are Google Scholar, IEEE Xplore, PubMed, Science Direct, Scopus and Web of Science, taking into account as date of publication the last 10 years, from 2008 to the present. Several search criteria were established such as 'techniques' AND 'Data Mining' AND 'Mental Health', 'algorithms' AND 'Data Mining' AND 'dementia' AND 'schizophrenia' AND 'depression', etc. selecting the papers of greatest interest. A total of 211 articles were found related to techniques and algorithms of Data Mining applied to the main Mental Health diseases. 72 articles have been identified as relevant works of which 32% are Alzheimer's, 22% dementia, 24% depression, 14% schizophrenia and 8% bipolar disorders. Many of the papers show the predict...Continue Reading

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Citations

Sep 18, 2018·Current Psychiatry Reports·Margarita AlegríaKiara Alvarez
Apr 6, 2019·Journal of Medical Internet Research·Andreas K Triantafyllidis, Athanasios Tsanas
Sep 12, 2020·Suicide & Life-threatening Behavior·Philip ResnikBeau Pinkham
Nov 17, 2020·Healthcare Informatics Research·Mehrdad KarajizadehAli Pakdam
Feb 17, 2021·Brain Informatics·Xiaohui TaoJiajin Huang
Apr 14, 2021·Journal of Medical Internet Research·Israel Júnior Borges do NascimentoDavid Novillo-Ortiz
Jun 17, 2021·JMIR Medical Informatics·Susel Góngora AlonsoIsabel De la Torre Díez
Aug 5, 2021·Scientific Reports·Hamid Reza MaratebRoya Kelishadi

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