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Intelligent decision support for real time health care monitoring system

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86097014" target="_blank" >RIV/61989100:27240/15:86097014 - isvavai.cz</a>

  • Alternative codes found

    RIV/61989100:27740/15:86097014

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-319-13572-4_15" target="_blank" >http://dx.doi.org/10.1007/978-3-319-13572-4_15</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-13572-4_15" target="_blank" >10.1007/978-3-319-13572-4_15</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Intelligent decision support for real time health care monitoring system

  • Original language description

    In the health care monitoring, data mining is mainly used for classification and predicting the diseases. Various data mining techniques are available for classification and predicting diseases. This paper analyzes and evaluates various classification techniques for decision support system and for assisting an intelligent health monitoring system. The aim of this paper is to investigate the experimental results of the performance of different classification techniques for classifying the data from different wearable sensors used for monitoring different diseases. The Base Classifiers Proposed used in this work are IBk, Attribute Selected Classifier, Bagging, PART, J48, LMT, Random Forest and the Random Tree algorithm. Experiments are conducted on wearable sensors vital signs data set, which was simulated using a hospital environment. The main focus was to reduce the dimensionality of the attributes and perform different comparative analysis and evaluation using various evaluation metho

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: IT4Innovations Centre of Excellence</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2015

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Advances in Intelligent Systems and Computing. Volume 334

  • ISBN

    978-3-319-13571-7

  • ISSN

    2194-5357

  • e-ISSN

  • Number of pages

    10

  • Pages from-to

    183-192

  • Publisher name

    Springer

  • Place of publication

    Heidelberg

  • Event location

    Addis Ababa

  • Event date

    Nov 17, 2014

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article