Search Articles

View query in Help articles search

Search Results (1 to 10 of 1335 Results)

Download search results: END BibTex RIS


Context-Sensitive Ecological Momentary Assessment: Application of User-Centered Design for Improving User Satisfaction and Engagement During Self-Report

Context-Sensitive Ecological Momentary Assessment: Application of User-Centered Design for Improving User Satisfaction and Engagement During Self-Report

Although participants using V3-simple received a single auditory alert, participants testing V3-ding received 2 additional auditory alerts when the first EMA question in a group was received by the mobile phone.

Preethi Srinivas, Kunal Bodke, Susan Ofner, NiCole R Keith, Wanzhu Tu, Daniel O Clark

JMIR Mhealth Uhealth 2019;7(4):e10894

Correction: Real-Time Forecasting of the COVID-19 Outbreak in Chinese Provinces: Machine Learning Approach Using Novel Digital Data and Estimates From Mechanistic Models

Correction: Real-Time Forecasting of the COVID-19 Outbreak in Chinese Provinces: Machine Learning Approach Using Novel Digital Data and Estimates From Mechanistic Models

Approach Using Novel Digital Data and Estimates From Mechanistic Models” (J Med Internet Res 2020;22(8):e20285) the authors noted three errors.The order of authors in the original article was listed as:Canelle Poirier, Dianbo Liu, Leonardo Clemente, Xiyu Ding

Dianbo Liu, Leonardo Clemente, Canelle Poirier, Xiyu Ding, Matteo Chinazzi, Jessica Davis, Alessandro Vespignani, Mauricio Santillana

J Med Internet Res 2020;22(9):e23996

Measurement Properties of the Online EuroQol-5D-Youth Instrument in Children and Adolescents With Type 1 Diabetes Mellitus: Questionnaire Study

Measurement Properties of the Online EuroQol-5D-Youth Instrument in Children and Adolescents With Type 1 Diabetes Mellitus: Questionnaire Study

There are several studies assessing the metric properties of the EQ-5D-Y in the general population [11,12] or in school environments [13-16]. A Swedish study [12] suggested that the EQ-5D-Y was comprehensible, acceptable, and feasible for self-completion.

Karina Mayoral, Luis Rajmil, Marta Murillo, Olatz Garin, Angels Pont, Jordi Alonso, Joan Bel, Jacobo Perez, Raquel Corripio, Gemma Carreras, Javier Herrero, Jose-Maria Mengibar, Dolors Rodriguez-Arjona, Ulrike Ravens-Sieberer, Hein Raat, Vicky Serra-Sutton, Montse Ferrer

J Med Internet Res 2019;21(11):e14947

Identifying Key Predictors of Cognitive Dysfunction in Older People Using Supervised Machine Learning Techniques: Observational Study

Identifying Key Predictors of Cognitive Dysfunction in Older People Using Supervised Machine Learning Techniques: Observational Study

Ding et al [20] used a Bayesian network approach for the classification of Alzheimer disease with heterogeneous features from the AIBL data set and demonstrated that machine learning could be used to select features and their appropriate combinations that are

Debbie Rankin, Michaela Black, Bronac Flanagan, Catherine F Hughes, Adrian Moore, Leane Hoey, Jonathan Wallace, Chris Gill, Paul Carlin, Anne M Molloy, Conal Cunningham, Helene McNulty

JMIR Med Inform 2020;8(9):e20995