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Journal of Emergency Nursing|December 19, 2018
Lack of Significant Coronary History and ECG Misinterpretation Are the Strongest Predictors of Undertriage in Prehospital Chest PainZiad Faramand, Stephanie O Frisch, Amber DeSantis, et al.The Journal of Emergency Medicine|October 17, 2019
Prevalence and Predictors of Delay in Seeking Emergency Care in Patients Who Call 9-1-1 for Chest PainStephanie O Frisch, Ziad Faramand, Hongjin Li, et al.European Journal of Emergency Medicine : Official Journal of the European Society for Emergency Medicine|September 18, 2020
Association between history of cancer and major adverse cardiovascular events in patients with chest pain presenting to the emergency department: a secondary analysis of a prospective cohort studyZiad Faramand, Hongjin Li, Nada Al-Rifai, et al.Heart & Lung : the Journal of Critical Care|October 13, 2018
Nonspecific electrocardiographic abnormalities are associated with increased length of stay and adverse cardiac outcomes in prehospital chest painDiana Rivero, Mohammad Alhamaydeh, Ziad Faramand, et al.International Journal of Medical Informatics|January 1, 2022
Engaging clinicians early during the development of a graphical user display of an intelligent alerting system at the bedsideStephanie Helman, Martha Ann Terry, Tiffany Pellathy, et al.Journal of Electrocardiology|September 1, 2021
Performance and limitations of automated ECG interpretation statements in patients with suspected acute coronary syndromeZiad Faramand, Stephanie Helman, Abdullah Ahmad, et al.BMC Medical Informatics and Decision Making|September 30, 2025
Prediction of atrial fibrillation admissions in arrhythmia naïve patients from structured electronic health record dataTanmay Gokhale, Nirav R Bhatt, Matthew Starr, et al.Journal of Electrocardiology|August 1, 2021
Novel ECG features and machine learning to optimize culprit lesion detection in patients with suspected acute coronary syndromeZeineb Bouzid, Ziad Faramand, Richard E Gregg, et al.Physiological Measurement|March 24, 2023
Integrating multimodal information in machine learning for classifying acute myocardial infarctionRan Xiao, Cheng Ding, Xiao Hu, et al.Journal of the American Heart Association|January 18, 2021
In Search of an Optimal Subset of ECG Features to Augment the Diagnosis of Acute Coronary Syndrome at the Emergency DepartmentZeineb Bouzid, Ziad Faramand, Richard E Gregg, et al.Pageof 3