Bio
Gabrielle Bunney, MD, MBA, MS is a Clinical Assistant Professor in the department of Emergency Medicine at Stanford University. She has a passion for using artificial intelligence (AI) models to support emergency medicine care delivery and efficiency. She has worked on projects spanning the whole life cycle in AI for clinical use, from model design and building, to model optimization, and finally the technical and clinical translation of AI for use in patient care. Her current research is focused on designing a model to select patients efficiently and equitably for an early electrocardiogram to detect myocardial infarction.
She received her Master’s degree from Stanford University’s Department of Biomedical Data Science, where she gained data science the technical experience to apply to her clinical knowledge. Additionally, she holds an MBA from the Kellogg School of Management with a focus in finance and is working with groups at Stanford that are bridging the gap between academic medicine and industry. She is a part of the Stanford Emergency Medicine Partnership Program (STEPP) aimed at building collaborations between the emergency department and companies focused on patient care solutions. The combination of a business background and research skills allow her to focus on the implementation of AI technologies into practice. She is continuing working on AI in healthcare with the philosophy that at the heart of innovation there must be a confluence of the strategic vision of the healthcare organization, economic viability, and practical operationalization.
Clinical Focus
- Emergency Medicine
Professional Education
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MS, Department of Biomedical Data Science, Stanford University School of Medicine (2024)
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MBA, Kellogg School of Management, Northwestern University (2022)
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Board Certification: American Board of Emergency Medicine, Emergency Medicine (2023)
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Residency: Northwestern University Emergency Medicine Residency (2022) IL
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Medical Education: Temple University School of Medicine Registrar (2018) PA