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The Effect of a Remote Network Technology Supervised Exercise Program Combined With Drug Treatment for Fibromyalgia: Randomized, Single-Blind, Controlled Trial

The Effect of a Remote Network Technology Supervised Exercise Program Combined With Drug Treatment for Fibromyalgia: Randomized, Single-Blind, Controlled Trial

This is likely due to the conservative nature of the Bonferroni correction, which adjusts the significance threshold to reduce the risk of type I errors. The loss of significance at certain time points suggests that some initial findings may have been false positives, and the remaining significant results after correction should be prioritized in the interpretation of the study outcomes.

Cuomaoji Zhang, Peijun Zhang, Yuanmeng Zhao, Yuntao Liu, Yun Hu, Zihan Zhu, Hong Xiao

J Med Internet Res 2025;27:e71624

Leveraging Artificial Intelligence for Digital Symptom Management in Oncology: The Development of CRCWeb

Leveraging Artificial Intelligence for Digital Symptom Management in Oncology: The Development of CRCWeb

In Phase I, 11 patients with CRC, 8 caregivers, and 4 oncologists were asked about their perspectives and suggestions for a technology-based intervention to manage symptoms. We gathered their feedback before the platform’s development. This early involvement of key users allowed us to ensure that the platform would be designed to address their specific needs, challenges, and expectations from the outset. During the interview, the participants were guided by the questions in Table 1.

Darren Liu, Yufen Lin, Runze Yan, Zhiyuan Wang, Delgersuren Bold, Xiao Hu

JMIR Cancer 2025;11:e68516

Predictive Performance of Machine Learning for Suicide in Adolescents: Systematic Review and Meta-Analysis

Predictive Performance of Machine Learning for Suicide in Adolescents: Systematic Review and Meta-Analysis

Heterogeneity across studies was assessed via the I² statistic. When the I² value was >50%, a random effects model was adopted to summarize the AUC, and when the I² value was Moreover, a meta-analysis was conducted on the sensitivity and specificity of ML in predicting suicide-related events using diagnostic 2×2 tables. A bivariate mixed effects model was employed.

Lingjiang Liu, Zhiyuan Li, Yaxin Hu, Chunyou Li, Shuhan He, Shibei Zhang, Jie Gao, Huaiyi Zhu, Guoping Huang

J Med Internet Res 2025;27:e73052