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Association Between Risk Factors and Major Cancers: Explainable Machine Learning Approach

Association Between Risk Factors and Major Cancers: Explainable Machine Learning Approach

Such insights can contribute to enhanced risk monitoring and patient stratification and provide valuable support for clinicians in their decision-making processes, ultimately improving the quality patient care. By elucidating these critical factors and their associated risk factor patterns, we provided clinicians valuable insights through rigorous analysis for enhancing risk monitoring and patient care across various cancer types.

Xiayuan Huang, Shushun Ren, Xinyue Mao, Sirui Chen, Elle Chen, Yuqi He, Yun Jiang

JMIR Cancer 2025;11:e62833

Agreement Between AI and Nephrologists in Addressing Common Patient Questions About Diabetic Nephropathy: Cross-Sectional Study

Agreement Between AI and Nephrologists in Addressing Common Patient Questions About Diabetic Nephropathy: Cross-Sectional Study

However, many turn to artificial intelligence (AI) models, like Chat GPT and Google Gemini, for web-based medical information [2-4]. To evaluate the capabilities of Chat GPT-4 and Google Gemini versus nephrologists in providing accurate DN information, their performance in answering the DN-related questions most commonly raised by patients was assessed.

Niloufar Ebrahimi, Mehrbod Vakhshoori, Seigmund Teichman, Amir Abdipour

JMIR Diabetes 2025;10:e65846

The Impact of Online Labor Platforms on Workforce Management in Health Care

The Impact of Online Labor Platforms on Workforce Management in Health Care

In the United States, platforms such as Nomad, Medely, Snap Care, and Care Rev have embraced the concept of temporary work by using web-based tools to connect hospitals with doctors and nurses for flexible, short-term assignments. Similarly, in Switzerland, web-based platforms like Careanesth, Coople, and Adecco serve as prominent avenues for the recruitment of temporary health care professionals. Figure 1 shows the rising trend of annual shift bookings on Careanesth from 2016 to 2022.

Maryam Ahmadi Shad, Michael Simon, Florian Liberatore

Interact J Med Res 2025;14:e68546

Family Members’ Experiences of a Person-Centered Information and Communication Technology–Supported Intervention for Stroke Rehabilitation (F@ce 2.0): Qualitative Analysis

Family Members’ Experiences of a Person-Centered Information and Communication Technology–Supported Intervention for Stroke Rehabilitation (F@ce 2.0): Qualitative Analysis

(https://feps-europe.eu/wp-content/uploads/2023/03/FEPS-FES_Care-Strategy-Policy-Study-web-PP.pdf) Reference 20: Use of mobile/tablet and web-based applications to support rehabilitation after stroke: Year 2021 - 2023 [Web page in Swedish](https://www.statistikdatabasen.scb.se/pxweb/sv/ssd/START__LE__

Gunilla Eriksson, Kajsa Söderhielm, Malin Erneby, Susanne Guidetti

JMIR Rehabil Assist Technol 2025;12:e69878

Assessing a Digital Tool to Screen and Educate Survivors of Domestic Violence on Affordable Housing Programs in New York City: Protocol for a Mixed Methods Feasibility Study

Assessing a Digital Tool to Screen and Educate Survivors of Domestic Violence on Affordable Housing Programs in New York City: Protocol for a Mixed Methods Feasibility Study

Knowing the above, the study team collaborated with a coalition of domestic violence housing specialists in New York City to create a web-based tool that both screens and educates survivors on affordable housing programs in New York City. Grounded in the process of empowerment [28], the digital tool strives to address survivors’ barriers to housing knowledge while building survivors’ self-efficacy to achieve their housing goals.

Jennifer K Tan, Michelle R Kaufman

JMIR Res Protoc 2025;14:e63162

Development of a Predictive Model for Metabolic Syndrome Using Noninvasive Data and its Cardiovascular Disease Risk Assessments: Multicohort Validation Study

Development of a Predictive Model for Metabolic Syndrome Using Noninvasive Data and its Cardiovascular Disease Risk Assessments: Multicohort Validation Study

This approach, which allows patients to easily check their current health status, raises awareness about their health, and provides appropriate management through web- or app-based platforms, can be effective in helping patients lead healthier lives [34-36].

Jin-Hyun Park, Inyong Jeong, Gang-Jee Ko, Seogsong Jeong, Hwamin Lee

J Med Internet Res 2025;27:e67525

Translation, Cross-Cultural Adaptation, and Psychometric Validation of the Health Information Technology Usability Evaluation Scale in China: Instrument Validation Study

Translation, Cross-Cultural Adaptation, and Psychometric Validation of the Health Information Technology Usability Evaluation Scale in China: Instrument Validation Study

To bridge this gap, Yen et al [15] developed the Health Information Technology Usability Evaluation Scale (Health-ITUES) based on Bidshift, a web-based communication system for scheduling nursing staff to improve the efficiency and effectiveness of the staffing and scheduling process. Bidshift allows nurse managers to announce open shifts throughout the organization and staff nurses to request shifts. 

Rongrong Guo, Ziling Zheng, Fangyu Yang, Ying Wu

J Med Internet Res 2025;27:e67948

The Longitudinal Effect of Psychological Distress on Internet Addiction Symptoms Among Chinese College Students: Cross-Lagged Panel Network Analysis

The Longitudinal Effect of Psychological Distress on Internet Addiction Symptoms Among Chinese College Students: Cross-Lagged Panel Network Analysis

Moreover, the IAT-20 scale used in this study does not distinguish between different types of internet use, such as social media, web browsing, online shopping, or gaming. Future research should explore these specific subdomains and examine their distinct relationships with mental health.

Yuxuan Jiang, Chuman Xiao, Xiang Wang, Dongling Yuan, Qian Liu, Yan Han, Jie Fan, Xiongzhao Zhu

J Med Internet Res 2025;27:e70680