AI Health Spark Seminar Series: Towards solving breast cancer diagnosis with deep learning
Although deep learning has made stunning progress in the last few years, both in terms of engineering and theory, its real-life applications in medicine remain rather limited. One of the fields that has been anticipated to be revolutionized by deep learning for some time, yet proved to be much harder than many expected, is medical imaging. In this talk I will shed some light on my 7-year long journey in developing deep learning methods for medical imaging, in particular, for breast cancer screening. I will explain how we created a deep learning model that can perform a diagnosis with an accuracy comparable to experienced radiologists. To achieve this goal we needed a lot of perseverance, novel neural network architectures and training methods specific to medical imaging. I will also discuss the limitations of our work and what can likely be achieved in the next few years.
This session is a part of the monthly seminar series organized by Spark: AI Health Initiative for Medical Imaging. The seminar will highlight outstanding work in medical imaging at Duke and beyond. The seminar recordings will be publicly available.
The Spark initiative focuses on development, validation, and clinical implementation of artificial intelligence algorithms for broadly understood medical imaging by bringing together the technical and clinical expertise across Duke campus. For more information please contact Dr. Maciej Mazurowski (email@example.com).