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

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...

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Publicado en:Journal of Medical Systems Vol. 42; no. 9; pp. 1 - 2
Autores principales: Alonso, Susel Góngora, de la Torre-Díez, Isabel, Hamrioui, Sofiane, López-Coronado, Miguel, Barreno, Diego Calvo, Nozaleda, Lola Morón, Franco, Manuel
Formato: research systematic review tables/charts Journal Article
Publicado: Springer Nature Sep2018
Acceso en línea:Ver este registro en EBSCOhost
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          Alonso, Susel Góngora
          de la Torre-Díez, Isabel
          Hamrioui, Sofiane
          López-Coronado, Miguel
          Barreno, Diego Calvo
          Nozaleda, Lola Morón
          Franco, Manuel
        affil: Department of Signal Theory and Communications, and Telematics Engineering, University of Valladolid, Paseo de Belén, 15, 47011, Valladolid, Spain
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        subj:
          Data Mining
          Algorithms
          Mental Disorders
          Dementia
          Human
          Systematic Review
          PubMed
          Web Search Engines
          Mental Disorders Risk Factors
          Depression
          Schizophrenia
          Bipolar Disorder
      ab: 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 prediction of risk factors in these diseases. From the review of the research articles analyzed, it can be said that use of Data Mining techniques applied to diseases such as dementia, schizophrenia, depression, etc. can be of great help to the clinical decision, diagnosis prediction and improve the patient’s quality of life.
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    language: English
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