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A Brief Cognitive Behavioral Therapy–Based Digital Intervention for Reducing Hazardous Alcohol Use in South Korea: Development and Prospective Pilot Study

Manjae Kwon, Daa Un Moon, Minjae Kang, Young-Chul Jung

JMIR Form Res 2025;9:e64459

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Text Messaging Interventions for Unhealthy Alcohol Use in Emergency Departments: Mixed Methods Assessment of Implementation Barriers and Facilitators

Megan O'Grady, Laura Harrison, Adekemi Suleiman, Morica Hutchison, Nancy Kwon, Frederick Muench, Sandeep Kapoor

JMIR Form Res 2025;9:e65187

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Machine Learning–Based Prediction of Substance Use in Adolescents in Three Independent Worldwide Cohorts: Algorithm Development and Validation Study

Soeun Kim, Hyejun Kim, Seokjun Kim, Hojae Lee, Ahmed Hammoodi, Yujin Choi, Hyeon Jin Kim, Lee Smith, Min Seo Kim, Guillaume Fond, Laurent Boyer, Sung Wook Baik, Hayeon Lee, Jaeyu Park, Rosie Kwon, Selin Woo, Dong Keon Yon

J Med Internet Res 2025;27:e62805

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Changes in Internet Activities and Influencing Factors for Problematic Internet Use During the COVID-19 Pandemic in Korean Adolescents: Repeated Cross-Sectional Study

Sol I Kim, Jae-Chan Jin, Seo-Koo Yoo, Doug Hyun Han

JMIR Pediatr Parent 2025;8:e66448

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Correction: Early Prediction of Cardiac Arrest in the Intensive Care Unit Using Explainable Machine Learning: Retrospective Study

Yun Kwan Kim, Won-Doo Seo, Sun Jung Lee, Ja Hyung Koo, Gyung Chul Kim, Hee Seok Song, Minji Lee

J Med Internet Res 2024;26:e67135

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Information and Communications Technology–Based Monitoring Service for Tailored Chronic Disease Management in Primary Care: Cost-Effectiveness Analysis Based on ICT-CM Trial Results

Sung-Hee Oh, Jae-Heon Kang, Jin-Won Kwon

J Med Internet Res 2024;26:e51239

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Early Prediction of Cardiac Arrest in the Intensive Care Unit Using Explainable Machine Learning: Retrospective Study

Kwon et al [17] proposed a deep learning–based early warning system that utilizes a recurrent neural network (RNN) to assess risk scores from input vectors measured over an 8-hour period. Their system, based on vital signs extracted from a retrospective multicenter cohort data set, resulted in AUROC and AUPRC values of 0.85 and 0.04, respectively.

Yun Kwan Kim, Won-Doo Seo, Sun Jung Lee, Ja Hyung Koo, Gyung Chul Kim, Hee Seok Song, Minji Lee