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Generative AI in Medicine: Pioneering Progress or Perpetuating Historical Inaccuracies? Cross-Sectional Study Evaluating Implicit Bias

Generative AI in Medicine: Pioneering Progress or Perpetuating Historical Inaccuracies? Cross-Sectional Study Evaluating Implicit Bias

If consensus could not be reached, the photo was classified as “other or unknown.” Photos determined to be insufficient to evaluate (images with a heavily obscured or no face) were excluded from analysis. Gender was classified as “man,” “woman,” and “other or unknown.” Race was classified as “Asian,” “Black,” “White” and “other or unknown.”

Philip Sutera, Rohini Bhatia, Timothy Lin, Leslie Chang, Andrea Brown, Reshma Jagsi

JMIR AI 2025;4:e56891

Research Dissemination Strategies in Pediatric Emergency Care Using a Professional Twitter (X) Account: A Mixed Methods Developmental Study of a Logic Model Framework

Research Dissemination Strategies in Pediatric Emergency Care Using a Professional Twitter (X) Account: A Mixed Methods Developmental Study of a Logic Model Framework

Events not mentioned in the NGT but felt to be crucial to the development of a social media account for dissemination, such as the incorporation of content creators and analytics managers, were then included in the development of our logic model.

Gwendolyn C Hooley, Julia N Magana, Jason M Woods, Shyam Sivasankar, Lauren VonHoltz, Anita R Schmidt, Todd P Chang, Michelle Lin

JMIR Form Res 2025;9:e59481

Integrating Mobile Health App Data Into Electronic Medical or Health Record Systems and Its Impact on Health Care Delivery and Patient Health Outcomes: Scoping Review

Integrating Mobile Health App Data Into Electronic Medical or Health Record Systems and Its Impact on Health Care Delivery and Patient Health Outcomes: Scoping Review

Over the past decade, significant progress has been made in developing interoperability frameworks that have the capacity to connect m Health solutions with electronic medical record (EMR, defined as a digital version of a patient’s medical chart within a single health care facility) or electronic health record (EHR, defined as a comprehensive digital record of a patient’s health that can be shared across multiple health care providers and facilities) systems [7-9].

Jialing Lin, Shona Marie Bates, Luke N Allen, Michael Wright, Limin Mao, Michael Kidd

JMIR Mhealth Uhealth 2025;13:e66650

Internet Health Information–Seeking Trend of Urinary Incontinence in Mainland China: Infodemiology Study

Internet Health Information–Seeking Trend of Urinary Incontinence in Mainland China: Infodemiology Study

It was reported that individuals with UI were more likely to conceal their distress and be hesitant to seek medical attention out of shame and stigma [11,12]. As a result, the known frequency of UI may be the tip of the iceberg [13,14].

Shuangquan Lin, Lingxing Duan, Xiongbing Lu, Haichao Chao, Xi Wen, Shanzun Wei

JMIR Form Res 2025;9:e55670

Digital Decision Aids to Support Decision-Making in Palliative and End-of-Life Dementia Care: Systematic Review and Meta-Analysis

Digital Decision Aids to Support Decision-Making in Palliative and End-of-Life Dementia Care: Systematic Review and Meta-Analysis

Patients found the Decide Guide valuable in decision-making, particularly they found the chat function to be powerful in helping members in their dementia care networks engage with one another constructively. Second is the PREPARE website.

Jie Zhong, Wei Liang, Tongyao Wang, Pui Hing Chau, Nathan Davies, Junqiang Zhao, Ho Nee Connie Chu, Chia Chin Lin

J Med Internet Res 2025;27:e71479

Development and Validation of a Predictive Model for Activities of Daily Living Dysfunction in Older Adults: Retrospective Analysis of Data From the China Health and Retirement Longitudinal Study

Development and Validation of a Predictive Model for Activities of Daily Living Dysfunction in Older Adults: Retrospective Analysis of Data From the China Health and Retirement Longitudinal Study

Informed by clinical experience and previous studies [11,12], we analyzed 46 potential variables that might be associated with the risk of ADL dysfunction. These variables spanned various domains, including demographic characteristics, health status, lifestyle factors, biochemical indicators, and functional status.

Fangbo Lin, Chao Liu, Hua Liu

JMIR Med Inform 2025;13:e73030

Development of a Machine Learning–Based Predictive Model for Postoperative Delirium in Older Adult Intensive Care Unit Patients: Retrospective Study

Development of a Machine Learning–Based Predictive Model for Postoperative Delirium in Older Adult Intensive Care Unit Patients: Retrospective Study

A list of all the variables used can be found in Textbox 1. Furthermore, to minimize the impact of missing data on the results, variables with more than 15% missing values were excluded from the final cohort (eg, height was excluded due to its 34.64% missing rate in our MIMIC-IV dataset).

Houfeng Li, Qinglai Zang, Qi Li, Yanchen Lin, Jintao Duan, Jing Huang, Huixiu Hu, Ying Zhang, Dengyun Xia, Miao Zhou

J Med Internet Res 2025;27:e67258

Evaluating the Characteristics and Outcomes of Acute Pharmaceutical Exposure in Children: 5-Year Retrospective Study

Evaluating the Characteristics and Outcomes of Acute Pharmaceutical Exposure in Children: 5-Year Retrospective Study

Furthermore, the clinical manifestations of acute poisoning in children are diverse, and some severe cases presenting consciousness disturbances and circulatory failure can be life-threatening.

Zhu Yan Duan, Yan Ning Qu, Rui Tang, Jun Ting Liu, Hui Wang, Meng Yi Sheng, Liang Liang Wang, Shuang Liu, Jiao Li, Lin Ying Guo, Si Zheng

JMIR Pediatr Parent 2025;8:e66951

Evaluating a Mobile Digital Therapeutic for Vasomotor and Behavioral Health Symptoms Among Women in Midlife: Randomized Controlled Trial

Evaluating a Mobile Digital Therapeutic for Vasomotor and Behavioral Health Symptoms Among Women in Midlife: Randomized Controlled Trial

The annual cost of menopausal symptoms in the United States alone is estimated to be US $26.6 billion, including US $1.8 billion due to productivity losses [10]. As the life expectancy of women continues to rise and midlife and older women make up one of the fastest-growing employment groups, it becomes increasingly important to address the considerable impact of menopausal symptoms through effective solutions [9,10].

Jennifer Duffecy, Arfa Rehman, Scott Gorman, Yong Lin Huang, Heide Klumpp

JMIR Mhealth Uhealth 2025;13:e58204

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

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