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Validation of an Infarction Code Care Checklist and Determination of its Relationship With Other Patient Safety Indicators: Protocol for a Prospective Study

Encarna Sanchez Freire, Josep Vidal Alaball, Aïna Fuster-Casanovas, Queralt Miró Catalina, Joan Cartanyà Bonvehí, Josep Lluis Garcia-Domingo

JMIR Res Protoc 2025;14:e66584

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Comparative Diagnostic Performance of a Multimodal Large Language Model Versus a Dedicated Electrocardiogram AI in Detecting Myocardial Infarction From Electrocardiogram Images: Comparative Study

Haemin Lee, Sooyoung Yoo, Joonghee Kim, Youngjin Cho, Dongbum Suh, Keehyuck Lee

JMIR AI 2025;4:e75910

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Barriers and Enablers to Routine Clinical Implementation of Cardiac Implantable Electronic Device Remote Monitoring in Australia Among Cardiologists, Cardiac Physiologists, Nurses, and Patients: Interview Study

Brodie Sheahen, Edel T O'Hagan, Kenneth Cho, Tim Shaw, Astin Lee, Sean Lal, Aaron L Sverdlov, Clara Chow

JMIR Cardio 2025;9:e67758

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Comparing the Performance of Machine Learning Models and Conventional Risk Scores for Predicting Major Adverse Cardiovascular Cerebrovascular Events After Percutaneous Coronary Intervention in Patients With Acute Myocardial Infarction: Systematic Review and Meta-Analysis

Min-Young Yu, Hae Young Yoo, Ga In Han, Eun-Jung Kim, Youn-Jung Son

J Med Internet Res 2025;27:e76215

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A Responsible Framework for Assessing, Selecting, and Explaining Machine Learning Models in Cardiovascular Disease Outcomes Among People With Type 2 Diabetes: Methodology and Validation Study

Yang Yang, Che-Yi Liao, Esmaeil Keyvanshokooh, Hui Shao, Mary Beth Weber, Francisco J Pasquel, Gian-Gabriel P Garcia

JMIR Med Inform 2025;13:e66200

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Large Language Models and Artificial Neural Networks for Assessing 1-Year Mortality in Patients With Myocardial Infarction: Analysis From the Medical Information Mart for Intensive Care IV (MIMIC-IV) Database

Boqun Shi, Liangguo Chen, Shuo Pang, Yue Wang, Shen Wang, Fadong Li, Wenxin Zhao, Pengrong Guo, Leli Zhang, Chu Fan, Yi Zou, Xiaofan Wu

J Med Internet Res 2025;27:e67253

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Harnessing an Artificial Intelligence–Based Large Language Model With Personal Health Record Capability for Personalized Information Support in Postsurgery Myocardial Infarction: Descriptive Qualitative Study

Ting-ting Yang, Hong-xia Zheng, Sha Cao, Mei-ling Jing, Ju Hu, Yan Zuo, Qing-yong Chen, Jian-jun Zhang

J Med Internet Res 2025;27:e68762

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Pharmacist-Initiated Team-Based Intervention for Optimizing Guideline-Directed Lipid Therapy of Hospitalized Patients With Acute Coronary Syndrome: Pilot Study Using a Stepped-Wedge Cluster Design

Gayle L Flo, Mateo Alzate Aguirre, Benjamin R Gochanour, Kristin J Hynes, Christopher G Scott, Angela L Fink, Adelaide M Arruda-Olson

JMIR Cardio 2025;9:e58837

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Assessment of the Sensitivity of a Smartphone App to Assist Patients in the Identification of Stroke and Myocardial Infarction: Cross-Sectional Study

Amar Dhand, Rama Mangipudi, Anubodh S Varshney, Jonathan R Crowe, Andria L Ford, Nancy K Sweitzer, Min Shin, Samuel Tate, Haissam Haddad, Michael E Kelly, James Muller, Jay S Shavadia

JMIR Form Res 2025;9:e60465

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Establishing Syndromic Surveillance of Acute Coronary Syndrome, Myocardial Infarction, and Stroke: Registry Study Based on Routine Data From German Emergency Departments

Madlen Schranz, Mirjam Rupprecht, Annette Aigner, Leo Benning, Carmen Schlump, Nesrine Charfeddine, Michaela Diercke, Linus Grabenhenrich, Alexander Ullrich, Hannelore Neuhauser, Birga Maier, AKTIN Research Group, Felix Patricius Hans, Sabine Blaschke

JMIR Public Health Surveill 2025;11:e66218

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