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Nonadherence to Diabetes Complications Screening in a Multiethnic Asian Population: Protocol for a Mixed Methods Prospective Study

Nonadherence to Diabetes Complications Screening in a Multiethnic Asian Population: Protocol for a Mixed Methods Prospective Study

Therefore, in this study, we focus on the implementation of phases 2-5 via a prospective, mixed methods study that combines a quantitative data collection phase followed by in-depth qualitative interviews. In Singapore, DM complications screening is performed mainly at 23 primary health care government polyclinics.

Amudha Aravindhan, Eva Fenwick, Aurora Wing Dan Chan, Ryan Eyn Kidd Man, Wern Ee Tang, Ngiap Chuan Tan, Charumathi Sabanayagam, Junxing Chay, Lok Pui Ng, Wei Teen Wong, Wern Fern Soo, Shin Wei Lim, Ecosse L Lamoureux

JMIR Res Protoc 2025;14:e63253

Diagnosis of Sarcopenia Using Convolutional Neural Network Models Based on Muscle Ultrasound Images: Prospective Multicenter Study

Diagnosis of Sarcopenia Using Convolutional Neural Network Models Based on Muscle Ultrasound Images: Prospective Multicenter Study

Convolutional neural networks (CNNs) are increasingly preferred due to their outstanding performance and high reproducibility in medical image analysis tasks [13]. Similarly, the objective, hard-to-quantify, and minor changes in ultrasound images on texture and volume in muscle may be quickly captured by CNN methods. Some CNN models using ultrasound images have exhibited remarkable capabilities in muscle segmentation, muscle function assessment, and myositis diagnosis [14-16].

Zi-Tong Chen, Xiao-Long Li, Feng-Shan Jin, Yi-Lei Shi, Lei Zhang, Hao-Hao Yin, Yu-Li Zhu, Xin-Yi Tang, Xi-Yuan Lin, Bei-Lei Lu, Qun Wang, Li-Ping Sun, Xiao-Xiang Zhu, Li Qiu, Hui-Xiong Xu, Le-Hang Guo

J Med Internet Res 2025;27:e70545

Multimodal Visualization and Explainable Machine Learning–Driven Markers Enable Early Identification and Prognosis Prediction for Symptomatic Aortic Stenosis and Heart Failure With Preserved Ejection Fraction After Transcatheter Aortic Valve Replacement: Multicenter Cohort Study

Multimodal Visualization and Explainable Machine Learning–Driven Markers Enable Early Identification and Prognosis Prediction for Symptomatic Aortic Stenosis and Heart Failure With Preserved Ejection Fraction After Transcatheter Aortic Valve Replacement: Multicenter Cohort Study

Detailed inclusion and exclusion criteria are provided in Table S1 in Multimedia Appendix 1, and the patient enrollment flowchart is depicted in Figure 1. The study was conducted in accordance with the Declaration of Helsinki. Flow diagram for patient selection. LVEF: left ventricular ejection fraction. In our study, we meticulously documented the clinical characteristics, comorbidities, laboratory findings, and echocardiographic observations for all enrolled patients.

Jun Wang, Jiajun Zhu, Hui Li, Shili Wu, Siyang Li, Zhuoya Yao, Tongjian Zhu, Bi Tang, Shengxing Tang, Jinjun Liu

J Med Internet Res 2025;27:e70587

Using Machine Learning to Predict Cognitive Decline in Older Adults From the Chinese Longitudinal Healthy Longevity Survey: Model Development and Validation Study

Using Machine Learning to Predict Cognitive Decline in Older Adults From the Chinese Longitudinal Healthy Longevity Survey: Model Development and Validation Study

In our study, SHAP was used to explain the predictive model for cognitive impairment in older adult individuals. SHAP values decompose the model’s prediction into individual contributions from each feature, making it possible to attribute the output to the various risk factors in a transparent and interpretable manner. The CLHLS was approved by the Duke University Institutional Review Board (Pro00062871) and the Peking University Biomedical Ethics Committee (IRB00001052–13074).

Hao Ren, Yiying Zheng, Changjin Li, Fengshi Jing, Qiting Wang, Zeyu Luo, Dongxiao Li, Deyi Liang, Weiming Tang, Li Liu, Weibin Cheng

JMIR Aging 2025;8:e67437

Evaluating the Effectiveness of Community-Delivered Hearing Rehabilitation and Health Education Intervention on Social Isolation and Functioning Among Chinese Adults With Hearing Impairment: Protocol for Randomized Controlled Trial

Evaluating the Effectiveness of Community-Delivered Hearing Rehabilitation and Health Education Intervention on Social Isolation and Functioning Among Chinese Adults With Hearing Impairment: Protocol for Randomized Controlled Trial

In response to the WHO’s guidelines on integrated person-centered ear and hearing care (IPC-EHC), we initiated the HISEA (Hearing Impairment and Social Outcomes Evaluation in Adults) project to conduct hearing interventions that targeted the social isolation and functioning of HI persons in Guangdong Province, China.

Jiamin Gao, Yuying Zhang, Xiaqing Jiang, Zhenjing Fu, Haochen Jiang

JMIR Res Protoc 2025;14:e64115

Real-Time, Risk-Based Clinical Trial Quality Management in China: Development of a Digital Monitoring Platform

Real-Time, Risk-Based Clinical Trial Quality Management in China: Development of a Digital Monitoring Platform

Over the past 20 years, with the improvement of the drug evaluation system and standards in China, an increasing number of domestic and cross-national multicenter clinical trials have been launched in Chinese hospitals. However, in many hospital-based clinical trial institutions, traditional quality management models largely rely on human monitoring and counting, which not only require a lot of time and resources but also likely result in errors and biases.

Min Jiang, Shuhua Zhao, Yun Mei, Zhiying Fu, Yannan Yuan, Jie Ai, Yuan Sheng, Ying Gong, Jingjing Chen

JMIR Med Inform 2025;13:e64114

Efficacy And Safety of Acupoint Catgut Embedding for Perennial Allergic Rhinitis: Protocol for a Randomized Clinical Trial

Efficacy And Safety of Acupoint Catgut Embedding for Perennial Allergic Rhinitis: Protocol for a Randomized Clinical Trial

ACE: acupoint catgut embedding; AE: adverse event; BRE: blood routine examination; FU: follow-up; RCAT: Rhinitis Control Assessment Test; RM: relief medication; TNSS: Total Nasal Symptom Score; TOSS: Total Ocular Symptom Score. Participants will be recruited via advertisements, posters, leaflets about the trial, and doctor referrals from otorhinolaryngology clinics in the 3 study hospitals. Interested individuals will need to contact research assistants by phone or email.

Zijie Cai, ChunXue Meng, Fei Wang, ChunZhi Tang, Jing Zhang, Qian Zhang, Bin Guo

JMIR Res Protoc 2025;14:e63933

Artificial Intelligence Models for Pediatric Lung Sound Analysis: Systematic Review and Meta-Analysis

Artificial Intelligence Models for Pediatric Lung Sound Analysis: Systematic Review and Meta-Analysis

Eight databases labeled lung pathologies including 6 studies that labeled a single lung pathology (pneumonia in 2 studies, asthma in 2 studies, bronchitis in 1 study, and CF in 1 study) and 2 studies that labeled multiple lung pathologies.

Ji Soo Park, Sa-Yoon Park, Jae Won Moon, Kwangsoo Kim, Dong In Suh

J Med Internet Res 2025;27:e66491

Enhancing Physician-Patient Communication in Oncology Using GPT-4 Through Simplified Radiology Reports: Multicenter Quantitative Study

Enhancing Physician-Patient Communication in Oncology Using GPT-4 Through Simplified Radiology Reports: Multicenter Quantitative Study

Similarly, studies by Doshi et al [2] focused on LLMs’ ability to streamline complex clinical information, making it more digestible for nonexpert users, particularly in the context of patient education. These studies have highlighted the improvements in readability but have largely neglected the application of LLMs in real-world clinical workflows, particularly regarding physician-patient communication and the broader impact on health care delivery, especially in oncology settings.

Xiongwen Yang, Yi Xiao, Di Liu, Huiyou Shi, Huiyin Deng, Jian Huang, Yun Zhang, Dan Liu, Maoli Liang, Xing Jin, Yongpan Sun, Jing Yao, XiaoJiang Zhou, Wankai Guo, Yang He, Weijuan Tang, Chuan Xu

J Med Internet Res 2025;27:e63786