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Visual Analytic Tools and Techniques in Population Health and Health Services Research: Scoping Review

Visual Analytic Tools and Techniques in Population Health and Health Services Research: Scoping Review

ministry, or health department35 (64)Abusharekh et al, 2015 [67]; Afzal et al, 2011 [85]; Alonso et al, 2012 [92]; Antunes de Mendonca et al, 2015 [86]; Baytas et al, 2016 [80]; Benis et al, 2017 [89]; Bryan et al, 2015 [64]; Castronovo et al, 2009 [77]; Chen

Jawad Ahmed Chishtie, Jean-Sebastien Marchand, Luke A Turcotte, Iwona Anna Bielska, Jessica Babineau, Monica Cepoiu-Martin, Michael Irvine, Sarah Munce, Sally Abudiab, Marko Bjelica, Saima Hossain, Muhammad Imran, Tara Jeji, Susan Jaglal

J Med Internet Res 2020;22(12):e17892


Use of Social Media by Western European Hospitals: Longitudinal Study

Use of Social Media by Western European Hospitals: Longitudinal Study

Countrya Number of hospitals Number of beds, mean (SD) Total General hospitals University hospitals NL 88 80 8 549 (278) BE 91 79 12 450 (261) LU 6 5 1 363 (139)

Tom H Van de Belt, Sivera AA Berben, Melvin Samsom, Lucien JLPG Engelen, Lisette Schoonhoven

J Med Internet Res 2012;14(3):e61


Training Cognitive Functions Using Mobile Apps in Breast Cancer Patients: Systematic Review

Training Cognitive Functions Using Mobile Apps in Breast Cancer Patients: Systematic Review

impairment in Alzheimer disease patients was the focus of the work of Zmily and colleagues [68], which focused on recall ability training to help individuals retain critical information longer and consequentially improve their quality of life.The research of Lu

Laura Vergani, Giulia Marton, Silvia Francesca Maria Pizzoli, Dario Monzani, Ketti Mazzocco, Gabriella Pravettoni

JMIR Mhealth Uhealth 2019;7(3):e10855


A Telesurveillance System With Automatic Electrocardiogram Interpretation Based on Support Vector Machine and Rule-Based Processing

A Telesurveillance System With Automatic Electrocardiogram Interpretation Based on Support Vector Machine and Rule-Based Processing

The algorithm by Chen et al [15] mainly applied morphology and background noise removal, and achieved a sensitivity of 99.7% and a detection error rate of 0.7%.

Te-Wei Ho, Chen-Wei Huang, Ching-Miao Lin, Feipei Lai, Jian-Jiun Ding, Yi-Lwun Ho, Chi-Sheng Hung

JMIR Med Inform 2015;3(2):e21