title: Schizophrenia prediction with the adaboost algorithm.
abstract: 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.
authors: Department of Cybernetics, Czech Technical University in Prague, The Czech Republic.
authors: Jan
authors: J
authors: Hrdlicka
authors: Jiri
authors: J
authors: Klema
mesh_terms: D000465:Algorithms; D001519:Behavior; D020000:Decision Support Systems, Clinical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006760:Hospitalization; D006801:Humans; D010349:Patient Compliance; D010359:Patient Readmission; D016730:Program Development / Q000379:methods; D012008:Recurrence; D019114:Remote Consultation / Q000379:methods*; D012559:Schizophrenia / Q000175:diagnosis* / Q000517:prevention & control; D012565:Schizophrenic Psychology; D012984:Software; D017216:Telemedicine / Q000379:methods*; D060145:Text Messaging; D013997:Time Factors