Machine Learning for Predicting Cognitive Diseases: Methods, Data Sources and Risk Factors.
Machine learning and data mining approaches are being successfully applied to different fields of life sciences for the past 20 years. Medicine is one of the most suitable application domains for these techniques since they help model diagnostic information based on causal and/or statistical data an...
| Publicado en: | Journal of Medical Systems Vol. 42; no. 12; pp. 1 - 2 |
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| Autores principales: | , , , , |
| Formato: | review tables/charts Journal Article |
| Publicado: |
Springer Nature
Dec2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=133352431&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 133352431 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Dec2018 vid: 42 iid: 12 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 133352431 133352431 133352431 10.1007/s10916-018-1071-x 133352431 ppf: 1 ppct: 1 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Machine Learning for Predicting Cognitive Diseases: Methods, Data Sources and Risk Factors. aug: au: Bratić, Brankica Kurbalija, Vladimir Ivanović, Mirjana Oder, Iztok Bosnić, Zoran affil: Faculty of Sciences, University of Novi Sad, Trg Dositeja Obradovića 4, Novi Sad, Serbia sug: subj: Machine Learning Methods Cognition Disorders Diagnosis Cognition Disorders Risk Factors Data Mining Risk Assessment Methods Alzheimer's Disease Diagnosis Parkinson Disease Diagnosis Alzheimer's Disease Risk Factors Magnetic Resonance Imaging Early Diagnosis Validity Patient Classification Cognition Disorders Classification Quality Improvement Questionnaires Scales ab: Machine learning and data mining approaches are being successfully applied to different fields of life sciences for the past 20 years. Medicine is one of the most suitable application domains for these techniques since they help model diagnostic information based on causal and/or statistical data and therefore reveal hidden dependencies between symptoms and illnesses. In this paper we give a detailed overview of the recent machine learning research and its applications for predicting cognitive diseases, especially the Alzheimer's disease, mild cognitive impairment and the Parkinson's disease. We survey different state-of-the-art methodological approaches, data sources and public data, and provide their comparative analysis. We conclude by identifying the open problems within the field that include an early detection of the cognitive diseases and inclusion of machine learning tools into diagnostic practice and therapy planning. pubtype: Academic Journal doctype: review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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