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Clinical Laboratory Parameter–Driven Machine Learning for Participant Selection in Bioequivalence Studies Among Patients With Gastric Cancer: Framework Development and Validation Study

Byungeun Shon, Sook Jin Seong, Eun Jung Choi, Mi-Ri Gwon, Hae Won Lee, Jaechan Park, Ho-Young Chung, Sungmoon Jeong, Young-Ran Yoon

JMIR AI 2025;4:e64845

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Current Technological Advances in Dysphagia Screening: Systematic Scoping Review

Duo Wai-Chi Wong, Jiao Wang, Sophia Ming-Yan Cheung, Derek Ka-Hei Lai, Armstrong Tat-San Chiu, Dai Pu, James Chung-Wai Cheung, Timothy Chi-Yui Kwok

J Med Internet Res 2025;27:e65551

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Effectiveness of Topic-Based Chatbots on Mental Health Self-Care and Mental Well-Being: Randomized Controlled Trial

Alan C Y Tong, Kent T Y Wong, Wing W T Chung, Winnie W S Mak

J Med Internet Res 2025;27:e70436

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Text-Based Depression Prediction on Social Media Using Machine Learning: Systematic Review and Meta-Analysis

Doreen Phiri, Frank Makowa, Vivi Leona Amelia, Yohane Vincent Abero Phiri, Lindelwa Portia Dlamini, Min-Huey Chung

J Med Internet Res 2025;27:e59002

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Effect of Continuous Positive Airway Pressure or Positional Therapy Compared to Control for Treatment of Obstructive Sleep Apnea on the Development of Gestational Diabetes Mellitus in Pregnancy: Protocol for Feasibility Randomized Controlled Trial

Biomarkers (s Flt-1 [soluble fms-like tyrosine kinase 1], Pl GF [placental growth factor], IL-6 [interleukin-6], TNFα [tumor necrosis factor alpha], and HIF1α [hypoxia-inducible factor 1-alpha]) will be assayed at the conclusion of the study blinded to outcomes. Urinalysis will be conducted at each study visit using SIEMENS Multistix 10 SG Test strips. A score of negative, trace, 30 mg/d L (++), 100 mg/d L (++), 300 mg/d L (++), or >2000 mg/d L (+++) will be recorded.

Frances Clements, Hima Vedam, Yewon Chung, John Smoleniec, Colin Sullivan, Renuka Shanmugalingam, Annemarie Hennessy, Angela Makris