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Authorship Correction: A Community-Based Short Message Service Intervention to Improve Mothers’ Feeding Practices for Obesity Prevention: Quasi-Experimental Study

Authorship Correction: A Community-Based Short Message Service Intervention to Improve Mothers’ Feeding Practices for Obesity Prevention: Quasi-Experimental Study

authors of “A Community-Based Short Message Service Intervention to Improve Mothers’ Feeding Practices for Obesity Prevention: Quasi-Experimental Study” (JMIR Mhealth Uhealth 2019;7(6):e13828) wish to change the order of the authors on the publication so that Xu

Hong Jiang, Mu Li, Li Ming Wen, Louise Baur, Gengsheng He, Xiaoying Ma, Xu Qian

JMIR Mhealth Uhealth 2019;7(7):e15046


Patient-Specific Predictive Modeling Using Random Forests: An Observational Study for the Critically Ill

Patient-Specific Predictive Modeling Using Random Forests: An Observational Study for the Critically Ill

Xu and colleagues have developed the case-specific random forest (CSRF) using the RF proximity measure as a bootstrap sampling weight [17].

Joon Lee

JMIR Med Inform 2017;5(1):e3


Measuring Audience Engagement for Public Health Twitter Chats: Insights From #LiveFitNOLA

Measuring Audience Engagement for Public Health Twitter Chats: Insights From #LiveFitNOLA

Xu et al revised their coding scheme (herein: Information-Community-Action [I-C-A] framework) to characterize tweets that included health-related hashtags [41,42].

Kristina M Rabarison, Merriah A Croston, Naomi K Englar, Connie L Bish, Shelbi M Flynn, Carolyn C Johnson

JMIR Public Health Surveill 2017;3(2):e34