AI News, Workshop Explores Impact of Artificial Intelligence on Radiology ... artificial intelligence

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When: Wednesday, October 16Time: 5:00PM-6:00PMLocation: Gates Building, Room 219Who it's for: All Stanford students, professors, and faculty **There will food/drinks provided, as well as a raffle for an NVIDIA Jetson Nano!

With key technologies like photo-realistic rendering, physics simulation and of course deep learning we are positioned perfectly to take one some of the hardest challenges around building intelligent machines.

Scenario Planning for The AI-Enabled Health System

As with many emerging technologies, it’s not easy to forecast the impact artificial intelligence will have on hospitals and health systems.

The report provides AI scenarios by looking at a preferred future (the future you want to see happen) and an undesired future (the one you don’t want to see).

This can help uncover which steps to take to reach the preferred future and how to avoid the undesired future.

Department of Computer Science, McCormick School of Engineering, Northwestern University

Deciphering a medical image is highly complex, requiring advanced medical knowledge, specialized technical skills, and case-by-case judgment.

The question drew more than 150 radiologists, engineers, and computer scientists for an all-day workshop on AI in radiology and medical decision-making on September 11.

The event included presentations on innovative approaches to using AI in radiology, case studies of problems facing radiologists aimed at informing AI researchers (and vice versa), lightning talks by Northwestern researchers, panel discussions, and networking opportunities.

In his keynote address, Curtis Langlotz, director of the Center for Artificial Intelligence in Medicine and Imaging at Stanford University, shared an example of a woman with congestive heart failure whose radiologist did not detect a small mass in her chest radiograph.

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