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Mobile Game–Based Digital Vaccine for Reducing Risk of Lifestyle Diseases

Mobile Game–Based Digital Vaccine for Reducing Risk of Lifestyle Diseases

Mellon UniversityPittsburgh, PAUnited States2Hofstra UniversityHampstead, NYUnited States3FriendsLearn, IncPalo Alto, CAUnited States4John Hopkins UniversityBaltimore, MDUnited States5The Mithra TrustChennaiIndia6Mind in MotionChennaiIndiaCorresponding Author: Yi-Chin

Rema Padman, Yi-Chin Kato-Lin, Bhargav SriPrakash, Sross Gupta, Palak Narang, Preethika Karthikeyan, Uttara Bharath-Kumar, Pradeep Krishnatray, Sanjeeta Agnihotri, Bhairavi Prakash, Vasini Varadan

iproc 2018;4(2):e11790

Using a Large Margin Context-Aware Convolutional Neural Network to Automatically Extract Disease-Disease Association from Literature: Comparative Analytic Study

Using a Large Margin Context-Aware Convolutional Neural Network to Automatically Extract Disease-Disease Association from Literature: Comparative Analytic Study

In PPI prediction, Peng and Lu’s CNN model achieved F scores of 63.5% on AIMed and 65.3% on BioInfer.For drug-drug interaction extraction, Lin et al [20] proposed a syntax CNN (SCNN) that integrates syntactic features, including words, predicates, and shortest

Po-Ting Lai, Wei-Liang Lu, Ting-Rung Kuo, Chia-Ru Chung, Jen-Chieh Han, Richard Tzong-Han Tsai, Jorng-Tzong Horng

JMIR Med Inform 2019;7(4):e14502

Accuracy of Parent-Reported Child Height and Weight and Calculated Body Mass Index Compared With Objectively Measured Anthropometrics: Secondary Analysis of a Randomized Controlled Trial

Accuracy of Parent-Reported Child Height and Weight and Calculated Body Mass Index Compared With Objectively Measured Anthropometrics: Secondary Analysis of a Randomized Controlled Trial

Subsequently, the child’s height and weight were measured at baseline and week 12 using standard protocols by blinded research assistants.In the laboratory sessions, child height was measured to the nearest 0.1 cm while the child was standing with their head and chin

Li Kheng Chai, Clare E Collins, Chris May, Carl Holder, Tracy L Burrows

J Med Internet Res 2019;21(9):e12532

Understanding Determinants of Health Care Professionals’ Perspectives on Mobile Health Continuance and Performance

Understanding Determinants of Health Care Professionals’ Perspectives on Mobile Health Continuance and Performance

Lin [17] reported a significant effect of the fit among technology (applicability, user interface, and portability), individual (computer self-efficacy, user experience, and self-immersion), and task (nonroutine, timeliness, interdependence, and mobility) characteristics

Ju-Ling Hsiao, Rai-Fu Chen

JMIR Med Inform 2019;7(1):e12350

Novel Approach to Cluster Patient-Generated Data Into Actionable Topics: Case Study of a Web-Based Breast Cancer Forum

Novel Approach to Cluster Patient-Generated Data Into Actionable Topics: Case Study of a Web-Based Breast Cancer Forum

equation model (Equation 3) for the MLR used is:Where topic1, topic2 are the weight scores of the topics in the files; εi is the error in the model; β0 is the intercept; β1, β2 are the coefficients for the topic1, topic2, respectively, computed by the model; and yi

Josette Jones, Meeta Pradhan, Masoud Hosseini, Anand Kulanthaivel, Mahmood Hosseini

JMIR Med Inform 2018;6(4):e45

Correction: Developing Theory-Driven, Evidence-Based Serious Games for Health: Framework Based on Research Community Insights

Correction: Developing Theory-Driven, Evidence-Based Serious Games for Health: Framework Based on Research Community Insights

The correct author of the book is Kato PM, instead of Arnab S. The correct reference is:Kato PM. The role of the researcher in making serious games for health. In: Arnab S, Debattista K, Dunwell I, editors.

Sarah Verschueren, Connor Buffel, Geert Vander Stichele

JMIR Serious Games 2020;8(2):e18515