Researchers from Lehigh University in Pennsylvania developed a diagnostic technique that combines deep learning and cutting-edge imaging technology to detect in real-time the difference between cancerous and benign cells with over 90% accuracy.
The Allen Institute for Cell Science launched a one-of-a-kind online portal of 3D cell images called Allen Cell Explorer that were produced using deep learning.
UK researchers developed a smartphone app using deep learning that lets people with Parkinson’s disease test their symptoms at home in just four minutes.
Todd Raeker, Research Technology Consultant at the University of Michigan shares how a group of 50 researchers at University of Michigan are using GPUs and OpenACC to accelerate the codes for their data-driven physics simulations.
Nicholas Bedworth, founder of SocialEyes, shares how they are developing cost-effective mobile AI diagnostic tools that can provide critically-needed medical services to low-resource societies.
Neurosurgeons and pathologists from University of Michigan Medicine developed a new imaging technique that can be used in the operating room to diagnose brain tumors more efficiently.
Late last year, the NVIDIA Inception Program hosted a “Cool Demo Contest” for GPU-accelerated startups that are applying deep learning to their innovations.
Le Lu, staff scientist at the National Institutes of Health (NIH) shares how they are applying artificial intelligence techniques to assist cancer clinicians make better diagnostic decisions. Using NVIDIA Tesla GPUs and the cuDNN-accelerated Caffe d
