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Schizophrenia Prediction with the Adaboost Algorithm

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F11%3A00183126" target="_blank" >RIV/68407700:21230/11:00183126 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Schizophrenia Prediction with the Adaboost Algorithm

  • Original language description

    This paper presents an adaBoost approach for schizophrenia relapse prediction. The data for the adaBoost are extracted from patients answers to Early Warning Signs questionnaires sent regularly via mobile phone messages. The performance of the adaBoost algorithm is confronted with current ITAREPS system with sensitivity 0.65 and specificity 0.73. AdaBoost has the same sensitivity 0.65 but higher specificity 0.84 and is then ready to became the part of the ITAREPS care program.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JC - Computer hardware and software

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2011

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    User Centred Networked Health Care

  • ISBN

    978-1-60750-805-2

  • ISSN

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    574-578

  • Publisher name

    IOS Press

  • Place of publication

    Amsterdam

  • Event location

    Oslo

  • Event date

    Aug 28, 2011

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article