An advanced artificial intelligence technique known as deep learning can predict major adverse cardiac events more accurately than current standard imaging protocols, according to research presented at the Society of Nuclear Medicine and Molecular Imaging 2021 Annual Meeting. Utilizing data from a registry of more than 20,000 patients, researchers developed a novel deep learning network that has the potential to provide patients with an individualized prediction of their annualized risk for adverse events.
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May 12, 2021
Congratulations class of 2021
This year marks the second virtual graduation ceremony for our general and advanced trainees. Here, eight fellows from five different countries: Natalija Odanovic, MD, Samuel W. Reinhardt, MD, Maen Abou Ziki, MD, Ehimen Aneni MD, MPH, Katherine Clark, MD, Jennifer M. Kwan MD, PhD, and Virginia Singla, MD, recollect the significant and lasting experiences from their training in cardiovascular medicine. A virtual webinar tentatively scheduled for June 10, 2021 will be held to celebrate our 26 graduates.
Natalija Odanovic, MD
I was born and raised in Belgrade, Serbia, where I had a carefree and magical childhood. I went to medical school (for free!) at the University of Belgrade Faculty of Medicine. I did my Internal Medicine Residency at Rutgers New Jersey Medical School where I had a wonderful time befriended many co-residents, learned a lot, and discovered my love for cardiology. Coming to Yale for fellowship was the perfect match for
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Lebanon
University-of-pennsylvania
California
Virginia
Lima
Peru
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