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Deep Learning for Radiologists: A Beginner's Guide

Deep learning is used in the research community and in industry to help solve many big data problems such as computer vision, speech recognition, and natural language processing.
Deep learning refers to a family of machine learning algorithms that make heavy use of artificial neural networks. In a 2016 Google Tech Talk, Jeff Dean describes deep learning algorithms as using very deep neural networks, where "deep" refers to the number of layers, or iterations between input and output. As computing power is becoming less expensive, the learning algorithms in today's applications are becoming "deeper." Machine Learning Definition. Retrieved from


Each month we post imaging pearls on various topics pertaining to deep learning such as artificial intelligence (AI), machine learning, radiomics, and more.

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Journal Club

Each month we post key articles in radiology and non-radiology journals on topics related to deep learning such as AI, machine learning, and more.

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Our discussion videos posted here focus on various topics of deep learning and AI relevant to radiology and medicine.

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Radiological Society of North America (RSNA) and American Roentgen Ray Society (ARRS) PowerPoint presentations and other exhibits on various topics pertaining to AI are posted here for self-learning. Please check frequently for updates.

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The Felix Project: A
Lustgarten Initiative

The Felix Project, funded by the Lustgarten Foundation, is a multidisciplinary research collaboration designed to use AI and deep learning to achieve earlier detection of pancreatic cancers on CT scans. This section includes the research papers that we are producing from this ambitious program.

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