A mobile health application to predict postpartum depression based on machine learning

Telemedicine and e-Health

Volumn 21, Issue 7, 2015, Pages 567-574

  Jiménez Serrano, Santiago ^a   Tortajada, Salvador ^a,b   García Gómez, Juan Miguel ^a,b  

^a UNIVERSITY OF VALENCIA   (Spain)

^b INSTITUTO DE INVESTIGACIÓN SANITARIA DEL HOSPITAL CLÍNICO SAN CARLOS IDISSC   (Spain)

Author keywords

Android; classifiers; Decision support; machine learning; mobile health; pattern recognition; postpartum depression

Indexed keywords

ANDROID (OPERATING SYSTEM); CLASSIFIERS; COST EFFECTIVENESS; DECISION SUPPORT SYSTEMS; E-LEARNING; GRAPHICAL USER INTERFACES; HEALTH RISKS; LEARNING SYSTEMS; MACHINE LEARNING; MHEALTH; PATIENT TREATMENT; PATTERN RECOGNITION; RISK PERCEPTION; SOFTWARE TESTING;

ANDROID; CLINICAL DECISION SUPPORT SYSTEMS; DECISION SUPPORTS; EVIDENCE- BASED DECISIONS; MACHINE LEARNING TECHNIQUES; MOBILE HEALTH APPLICATION; POSTPARTUM DEPRESSIONS; SENSITIVITY AND SPECIFICITY;

PREDICTIVE ANALYTICS;

ADULT; DEPRESSION, POSTPARTUM; FEMALE; FORECASTING; HUMAN; MACHINE LEARNING; PROSPECTIVE STUDY; QUESTIONNAIRE; RISK FACTOR; SENSITIVITY AND SPECIFICITY; TELEMEDICINE;

ADULT; DEPRESSION, POSTPARTUM; FEMALE; FORECASTING; HUMANS; MACHINE LEARNING; PROSPECTIVE STUDIES; RISK FACTORS; SENSITIVITY AND SPECIFICITY; SURVEYS AND QUESTIONNAIRES; TELEMEDICINE;

EID: 84936929209     PISSN: 15305627     EISSN: 15563669     Source Type: Journal    
DOI: 10.1089/tmj.2014.0113     Document Type: Article

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