Audible Bleeding editor Wen (@WenKawaji) is joined by first-year vascular surgery fellow Zach (@ZMatthay), 5th year integrated vascular surgery resident Kaitlyn (@DunphyKaitlyn), JVS editor Dr. Forbes (@TL_Forbes) and JVS-VS associate editor Dr. Curci (@CurciAAA) to discuss two great articles in the JVS family of journals regarding machine learning in carotid endarterectomy and abdominal aortic aneurysm. This episode hosts Dr.Li (@ben_li123), Dr. De Mestral (@vasc_surg), Dr. Kiang (@sharon_Kiang_MD), and Dr. Tomihama (@roger_tomihama), the authors of the following papers:
Articles:
- Using Machine Learning to predict outcomes following carotid endarterectomy by Li et al.
- Machine learning analysis of confounding variables of a convolutional neural network specific for abdominal aortic aneurysms by Tomihama et al
Show Guests:
- Dr. Li is a vascular surgery resident and PhD candidate at the University of Toronto
- Dr. De Mestral is an associate professor of vascular surgery at the University of Toronto who also has a PhD in health services research and focuses on clinical effectiveness, cost, and quality of surgical care.
- Dr. Sharon Kiang is the chief of vascular surgery at the Loma Linda Veteran’s affairs hospital as well as an associate professor and vice-chair of research of surgery at Loma Linda University. She is also the PI for the Center for Artificial Intelligence and Vascular Engineering.
- Dr. Roger Tomihama is an associate professor of interventional radiology with 18+ years of experience in clinical medicine, biomedical research, graduate medical education, and professional organizations. He was a former officer in the United States Navy and recipient of the Navy Commendation Medal. As a clinician scientist, he has procured $1.4 million dollars of extramural research grant funding, have 22 peer-reviewed publications, 4 invited publications, and 4 book chapters. His current research focus includes artificial intelligence in imaging for vascular disease. Lastly, he is currently pursuing a Master's of Business Administration at the Wharton School of Business at the University of Pennsylvania.
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