Treatment Trajectories Graph Compression Algorithm Based on Cliques...18th International Conference on Wearable Micro and Nano Technologies for Personalized Health (virtual), November 8-10, 2021.

Learning treatment methods and disease progression is significant part of medicine. Graph representation of data provides wide area for visualization and optimization of structure. Present work is dedicated to suggest method of data processing for increasing information interpretability. Graph compr...

Descripción completa

Detalles Bibliográficos
Publicado en:Studies in Health Technology & Informatics Vol. 285; pp. 300 - 306
Autores principales: MILYKH, Svetozar, KOVALCHUK, Sergey
Formato: proceedings research tables/charts Journal Article
Publicado: Sage Publications Inc. 2021
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=153525212&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 153525212
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        09269630
        U1V
      jtl: Studies in Health Technology & Informatics
      issn: 09269630
      maglogo: N
    pubinfo:
      dt: 2021
      vid: 285
      pid: 344
      pub: Sage Publications Inc.
      place: Thousand Oaks, California
    artinfo:
      ui:
        153525212
        153525212
        153525212
        10.3233/SHTI210620
        153525212
      ppf: 300
      ppct: 6
      formats:
      tig:
        atl: Treatment Trajectories Graph Compression Algorithm Based on Cliques...18th International Conference on Wearable Micro and Nano Technologies for Personalized Health (virtual), November 8-10, 2021.
      aug:
        au:
          MILYKH, Svetozar
          KOVALCHUK, Sergey
        affil: ITMO University, Saint Petersburg, Russia
      sug:
        subj:
          Algorithms
          Disease Progression
          Signal Processing, Computer Assisted
          Machine Learning
          Descriptive Statistics
          Coronary Angiography
          Human
          Funding Source
      ab: Learning treatment methods and disease progression is significant part of medicine. Graph representation of data provides wide area for visualization and optimization of structure. Present work is dedicated to suggest method of data processing for increasing information interpretability. Graph compression algorithm based on maximum clique search is applied to data set with acute coronary syndrome treatment trajectories. Results of compression are studied using graph entropy measures.
      pubtype: Academic Journal
      doctype:
        proceedings
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N