Use of Machine Learning Models for Classification of Myographic Diseases.

These studies addressed the problem of classification by applying sequential machine learning models using deep learning methods. Studies used the Kaggle platform and the Python programming language. The accuracy of the neural network, which depends on the number of epochs, was established using acc...

Descripción completa

Detalles Bibliográficos
Publicado en:Biomedical Engineering Vol. 56; no. 5; pp. 353 - 358
Autores principales: Abdullaev, N. T., Pashaeva, K. Sh.
Formato: computer program research tables/charts Journal Article
Publicado: Springer Nature Jan2023
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=161349913&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 161349913
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        00063398
        N96
      jtl: Biomedical Engineering
      issn: 00063398
      maglogo: N
    pubinfo:
      dt: Jan2023
      vid: 56
      iid: 5
      pid: 237
      pub: Springer Nature
      place: New York, New York
    artinfo:
      ui:
        161349913
        161251633
        161349913
        161349913
        10.1007/s10527-023-10234-6
        161349913
      ppf: 353
      ppct: 5
      formats:
      tig:
        atl: Use of Machine Learning Models for Classification of Myographic Diseases.
      aug:
        au:
          Abdullaev, N. T.
          Pashaeva, K. Sh.
        affil: Department of Biomedical Technology, Azerbaijan Technical University, Baku, Azerbaijan
      sug:
        subj:
          Machine Learning Utilization
          Deep Learning Methods
          Electromyography
          Programming Languages
          Neural Networks (Computer)
          Prediction Models
      ab: These studies addressed the problem of classification by applying sequential machine learning models using deep learning methods. Studies used the Kaggle platform and the Python programming language. The accuracy of the neural network, which depends on the number of epochs, was established using accuracy and training losses curves; the influence of the number of losses on increases in network accuracy is estimated.
      pubtype: Academic Journal
      doctype:
        computer program
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N