Artificial neural networks in neurorehabilitation: A scoping review.

BACKGROUND: Advances in medical technology produce highly complex datasets in neurorehabilitation clinics and research laboratories. Artificial neural networks (ANNs) have been utilized to analyze big and complex datasets in various fields, but the use of ANNs in neurorehabilitation is limited. OBJE...

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Publicado en:NeuroRehabilitation Vol. 46; no. 3; pp. 259 - 270
Autores principales: Moon, Sanghee, Ahmadnezhad, Pedram, Hyun-Je Song, Thompson, Jeffrey, Kipp, Kristof, Akinwuntan, Abiodun E., Devos, Hannes
Formato: research systematic review tables/charts Journal Article
Publicado: Sage Publications Inc. 2020
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 2020
      vid: 46
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      pub: Sage Publications Inc.
      place: Thousand Oaks, California
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        145378774
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        atl: Artificial neural networks in neurorehabilitation: A scoping review.
      aug:
        au:
          Moon, Sanghee
          Ahmadnezhad, Pedram
          Hyun-Je Song
          Thompson, Jeffrey
          Kipp, Kristof
          Akinwuntan, Abiodun E.
          Devos, Hannes
        affil: Department of Biostatistics, School of Medicine, University of Kansas Medical Center, Kansas City, KS, USA
      sug:
        subj:
          Nervous System Diseases Rehabilitation
          Neural Networks (Computer) Utilization
          Decision Making, Clinical
          Human
          Scoping Review
          PubMed
          CINAHL Database
          Cognition
          Functional Assessment
          Nervous System Diseases Mortality
          Nervous System Diseases Prognosis
      ab: BACKGROUND: Advances in medical technology produce highly complex datasets in neurorehabilitation clinics and research laboratories. Artificial neural networks (ANNs) have been utilized to analyze big and complex datasets in various fields, but the use of ANNs in neurorehabilitation is limited. OBJECTIVE: To explore the current use of ANNs in neurorehabilitation. METHODS: PubMed, CINAHL, and Web of Science were used for the literature search. Studies in the scoping review (1) utilized ANNs, (2) examined populations with neurological conditions, and (3) focused on rehabilitation outcomes. The initial search identified 1,136 articles. A total of 19 articles were included. RESULTS: ANNs were used for prediction of functional outcomes and mortality (n = 11) and classification of motor symptoms and cognitive status (n = 8). Most ANN-based models outperformed regression or other machine learning models (n = 11) and showed accurate performance (n = 6; no comparison with other models) in predicting clinical outcomes and accurately classifying different neurological impairments. CONCLUSIONS: This scoping review provides encouraging evidence to use ANNs for clinical decision-making of complex datasets in neurorehabilitation. However, more research is needed to establish the clinical utility of ANNs in diagnosing, monitoring, and rehabilitation of individuals with neurological conditions.
      pubtype: Academic Journal
      doctype:
        research
        systematic review
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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