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Improving Phenotyping of Patients With Immune-Mediated Inflammatory Diseases Through Automated Processing of Discharge Summaries: Multicenter Cohort Study

Improving Phenotyping of Patients With Immune-Mediated Inflammatory Diseases Through Automated Processing of Discharge Summaries: Multicenter Cohort Study

Our hypothesis was that incorporating the results of laboratory tests and drug treatments recorded in patients’ discharge summaries would complement the information available in structured data and enable more in-depth, interoperable phenotyping of patients, while remaining reliable. Overview of the end-to-end patient phenotyping pipeline.

Adam Remaki, Jacques Ung, Pierre Pages, Perceval Wajsburt, Elise Liu, Guillaume Faure, Thomas Petit-Jean, Xavier Tannier, Christel Gérardin

JMIR Med Inform 2025;13:e68704

Efficacy of a Personalized mHealth App in Improving Micronutrient Supplement Use Among Pregnant Women in Karachi, Pakistan: Parallel-Group Randomized Controlled Trial

Efficacy of a Personalized mHealth App in Improving Micronutrient Supplement Use Among Pregnant Women in Karachi, Pakistan: Parallel-Group Randomized Controlled Trial

On the other hand, the nonintervention group demonstrated significantly higher odds of sufficient calcium use (a OR 0.59, 95% CI 0.44-0.79; Table 9; Multimedia Appendix 1) Unadjusted and adjusted analysis of the efficacy of the intervention on sufficiency of supplement usea. a The nonintervention group is taken as a reference.

Khadija Vadsaria, Rozina Nuruddin, Nuruddin Mohammed, Iqbal Azam, Saleem Sayani

J Med Internet Res 2025;27:e67166

Factors Impacting Mobile Health Adoption for Depression Care and Support by Adolescent Mothers in Nigeria: Preliminary Focus Group Study

Factors Impacting Mobile Health Adoption for Depression Care and Support by Adolescent Mothers in Nigeria: Preliminary Focus Group Study

The age of mothers who had some high school education was 10.6 (SD 1.9) years: 8 out of 19 (42.1%) of them were still students, 2 out of 19 (10.5%) of these were first-year university undergraduates); and 11 out of 19 (57.8%) others had dropped out of school and engaged in petty trading. The care providers were middle-aged (mean 48, SD 5.8 years) majorly female (18/19, 95%), and with significant (mean 22.2, SD 4.7 years) work experience.

Lola Kola, Tobi Fatodu, Manasseh Kola, Bisola A Olayemi, Adeyinka O Adefolarin, Simpa Dania, Manasi Kumar, Dror Ben-Zeev

JMIR Form Res 2025;9:e42406

Young Adult Perspectives on Artificial Intelligence–Based Medication Counseling in China: Discrete Choice Experiment

Young Adult Perspectives on Artificial Intelligence–Based Medication Counseling in China: Discrete Choice Experiment

Medication adherence in young individuals cannot be improved by education alone. Increasing the number of behavioral components (eg, monitoring and goal setting, rewards, problem solving, linking medication taking to established procedures) may produce better results. Therefore, we started with established procedures to find out the preferred usage patterns of young people and to fill any gap.

Jia Zhang, Jing Wang, JingBo Zhang, XiaoQian Xia, ZiYun Zhou, XiaoMing Zhou, YiBo Wu

J Med Internet Res 2025;27:e67744

Extracting Pulmonary Embolism Diagnoses From Radiology Impressions Using GPT-4o: Large Language Model Evaluation Study

Extracting Pulmonary Embolism Diagnoses From Radiology Impressions Using GPT-4o: Large Language Model Evaluation Study

Moreover, the stability of the performance of GPT-4o in identifying pulmonary embolisms in various datasets suggests robustness and generality, which could be useful in various clinical settings. The employment of AI models in health care induces multifaceted ethical issues that need to be deliberated on. The first and foremost concern is the privacy of the patients and the security of the information because medical information is private.

Mohammed Mahyoub, Kacie Dougherty, Ajit Shukla

JMIR Med Inform 2025;13:e67706

Co-Designing a Web-Based and Tablet App to Evaluate Clinical Outcomes of Early Psychosis Service Users in a Learning Health Care Network: User-Centered Design Workshop and Pilot Study

Co-Designing a Web-Based and Tablet App to Evaluate Clinical Outcomes of Early Psychosis Service Users in a Learning Health Care Network: User-Centered Design Workshop and Pilot Study

The Early Psychosis Intervention Network of California (EPI-CAL) [4] was developed to support the provision of quality EPI services and to create an infrastructure to conduct standardized measurement of the impact of early psychosis care delivery. To support this goal, the EPI-CAL team, in collaboration with several California counties, developed a learning health care network (LHCN) consisting of EPI programs across the state.

Kathleen E Burch, Valerie L Tryon, Katherine M Pierce, Laura M Tully, Sabrina Ereshefsky, Mark Savill, Leigh Smith, Adam B Wilcox, Christopher Komei Hakusui, Viviana E Padilla, Amanda P McNamara, Merissa Kado-Walton, Andrew J Padovani, Chelyah Miller, Madison J Miles, Nitasha Sharma, Khanh Linh H Nguyen, Yi Zhang, Tara A Niendam

JMIR Hum Factors 2025;12:e65889

A Risk Prediction Model (CMC-AKIX) for Postoperative Acute Kidney Injury Using Machine Learning: Algorithm Development and Validation

A Risk Prediction Model (CMC-AKIX) for Postoperative Acute Kidney Injury Using Machine Learning: Algorithm Development and Validation

It is a common complication that affects up to 5% to 7.5% of all hospitalized patients, with a markedly higher prevalence of 20% in intensive care units [1]. Among all AKI in hospitalized patients, 40% occur in postoperative patients [1]. This condition not only escalates morbidity but also substantially increases in-hospital mortality by approximately 3- to 9-fold [2].

Ji Won Min, Jae-Hong Min, Se-Hyun Chang, Byung Ha Chung, Eun Sil Koh, Young Soo Kim, Hyung Wook Kim, Tae Hyun Ban, Seok Joon Shin, In Young Choi, Hye Eun Yoon

J Med Internet Res 2025;27:e62853

Developing a Machine Learning Model for Predicting 30-Day Major Adverse Cardiac and Cerebrovascular Events in Patients Undergoing Noncardiac Surgery: Retrospective Study

Developing a Machine Learning Model for Predicting 30-Day Major Adverse Cardiac and Cerebrovascular Events in Patients Undergoing Noncardiac Surgery: Retrospective Study

The SNUBH dataset contains data from 46,225 patients who underwent noncardiac surgery between January 2003 and December 2020, and the AMC dataset includes data from 396,424 patients who underwent noncardiac surgery between January 2010 and December 2020.

Ju-Seung Kwun, Houng-Beom Ahn, Si-Hyuck Kang, Sooyoung Yoo, Seok Kim, Wongeun Song, Junho Hyun, Ji Seon Oh, Gakyoung Baek, Jung-Won Suh

J Med Internet Res 2025;27:e66366

Factors Influencing Information Distortion in Electronic Nursing Records: Qualitative Study

Factors Influencing Information Distortion in Electronic Nursing Records: Qualitative Study

When unexpected events occur, they might be omitted from the records simply because they fall outside of the usual routine. Patients are a primary source of information, and much of the content in ENRs is based on their complaints. In clinical practice, patient-reported information is typically reflected accurately in ENRs.

Jianan Wang, Yihong Xu, Zhichao Yang, Jie Zhang, Xiaoxiao Zhang, Wen Li, Yushu Sun, Hongying Pan

J Med Internet Res 2025;27:e66959

A New Mobile App to Train Attention Processes in People With Traumatic Brain Injury: Logical and Ecological Content Validation Study

A New Mobile App to Train Attention Processes in People With Traumatic Brain Injury: Logical and Ecological Content Validation Study

The use of attentional focusing techniques of mindfulness could also be useful for the management of attention difficulties in people who have experienced moderate to severe TBI. Indeed, focusing on the present moment is a way of controlling one’s own attentional processes. As such, attention is considered central to the construct of mindfulness [10]. One limit of this type of intervention is access to a trained guide to accompany individuals, especially for people living in remote areas.

Roxanne Laverdière, Philip L Jackson, Frédéric Banville

JMIR Form Res 2025;9:e64174