Journal of Medical Internet Research

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Implementation of Health IT for Cancer Screening in US Primary Care: Scoping Review

Constance Owens-Jasey, Jinying Chen, Ran Xu, Heather Angier, Amy G Huebschmann, Mayuko Ito Fukunaga, Krisda H Chaiyachati, Katharine A Rendle, Kim Robien, Lisa DiMartino, Daniel J Amante, Jamie M Faro, Maura M Kepper, Alex T Ramsey, Eric Bressman, Rachel Gold

JMIR Cancer 2024;10:e49002

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Applying Machine Learning Techniques to Implementation Science

Nathalie Huguet, Jinying Chen, Ravi B Parikh, Miguel Marino, Susan A Flocke, Sonja Likumahuwa-Ackman, Justin Bekelman, Jennifer E DeVoe

Online J Public Health Inform 2024;16:e50201

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Monitoring the Implementation of Tobacco Cessation Support Tools: Using Novel Electronic Health Record Activity Metrics

Jinying Chen, Sarah L Cutrona, Ajay Dharod, Stephanie C Bunch, Kristie L Foley, Brian Ostasiewski, Erica R Hale, Aaron Bridges, Adam Moses, Eric C Donny, Erin L Sutfin, Thomas K Houston, iDAPT Implementation Science Center for Cancer Control

JMIR Med Inform 2023;11:e43097

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Understanding Patients’ Intention to Use Digital Health Apps That Support Postdischarge Symptom Monitoring by Providers Among Patients With Acute Coronary Syndrome: Survey Study

Jinying Chen, Jessica G Wijesundara, Gabrielle E Enyim, Lisa M Lombardini, Ben S Gerber, Thomas K Houston, Rajani S Sadasivam

JMIR Hum Factors 2022;9(1):e34452

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Detecting Hypoglycemia Incidents Reported in Patients’ Secure Messages: Using Cost-Sensitive Learning and Oversampling to Reduce Data Imbalance

Jinying Chen, John Lalor, Weisong Liu, Emily Druhl, Edgard Granillo, Varsha G Vimalananda, Hong Yu

J Med Internet Res 2019;21(3):e11990

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A Natural Language Processing System That Links Medical Terms in Electronic Health Record Notes to Lay Definitions: System Development Using Physician Reviews

Jinying Chen, Emily Druhl, Balaji Polepalli Ramesh, Thomas K Houston, Cynthia A Brandt, Donna M Zulman, Varsha G Vimalananda, Samir Malkani, Hong Yu

J Med Internet Res 2018;20(1):e26

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Ranking Medical Terms to Support Expansion of Lay Language Resources for Patient Comprehension of Electronic Health Record Notes: Adapted Distant Supervision Approach

We represented multiword terms (ie, compound terms) by the mean of the vectors of their component words by following Jagannatha et al [37] and Chen and colleagues [38,39]. We mapped candidate terms to UMLS concepts and included semantic types for those concepts that had an exact match or a head-noun match as features. Each semantic type is a 0-1 binary feature. This type of feature has been used to identify domain-specific medical terms [23,33] and to rank medical terms from individual EHR notes [38].

Jinying Chen, Abhyuday N Jagannatha, Samah J Fodeh, Hong Yu

JMIR Med Inform 2017;5(4):e42

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