DEEP TECH HEALTH + NEUROTECH
Viz.ai‘s algorithms analyze brain scans and immediately transfer data to ensure rapid stroke treatment. The system connects to a hospital CT and sends alerts when a suspected LVO stroke has been identified. Radiological images are sent to a doctor’s phone. The company claims that the median time from picture to notification is less than 6 […]
DARPA Biological Technologies Office Director Dr. Justin Sanchez on driving and reshaping biotechnology. Recorded at ApplySci’s Wearable Tech + Digital Health + Neurotech Silicon Valley conference on February 26-27, 2018 at Stanford University. Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 25, 2018 at the MIT Media […]
Vinod Khosla + Lisa Weiner Intrator discuss AI in healthcare at ApplySci’s Wearable Tech + Digital Health + Neurotech Silicon Valley conference – February 26-27, 2018 at Stanford University Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 25, 2018 at the MIT Media Lab
Cortical founder and former DARPA NESD program manager Phillip Alvelda discusses AI and the brain at ApplySci’s Wearable Tech + Digital Health + Neurotech Silicon Valley conference on February 26-27, 2018 at Stanford University: Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference – September 25, 2018 at the MIT Media […]
Google’s Lily Peng has developed an algorithm that can predict heart attacks and strokes by analyzing images of the retina. The system also shows which eye areas lead to successful predictions, which can provide insight into the causes of cardiovascular disease. The dataset consisted of 48,101 patients from the UK Biobank database and 236,234 patients […]
Nissan’s Brain-to-Vehicle (B2V) technology will enable vehicles to interpret signals from a driver’s brain. The company describes two aspects of the system — prediction and detection, which depend on a driver wearing EEG electrodes: Predicton: By detecting, via the brain, that the driver is about to move, including turning the steering wheel or pushing the […]
Sergey Levine and UC Berkeley colleagues have developed robotic learning technology that enables robots to visualize how different behaviors will affect the world around them, with out human instruction. This ability to plan, in various scenarios, could improve self-driving cars and robotic home assistants. Visual foresight allows robots to predict what their cameras will see if they perform […]
Andrew Ng and Stanford colleagues used AI to detect pneumonia from x-rays with similar accuracy to trained radiologists. The CheXNet model analyzed 112,200 frontal-view X-ray images of 30,805 unique patients released by the NIH (ChestX-ray14.) Deep Learning algorithms also detected14 diseases including fibrosis, hernias, and cell masses, with fewer false positives and negatives than NIH […]
Yuichi Mori and Showa University colleagues haved used AI to identify bowel cancer by analyzing colonoscopy derived polyps in less than a second. The system compares a magnified view of a colorectal polyp with 30,000 endocytoscopic images. The researchers claimed 86% accuracy, based on a study of 300 polyps. While further testing the technology, Mori said that […]
MIT’s Regina Barzilay has used AI to improve breast cancer detection and diagnosis. Machine learning tools predict if a high-risk lesion identified on needle biopsy after a mammogram will upgrade to cancer at surgery, potentially eliminating unnecessary procedures. In current practice, when a mammogram detects a suspicious lesion, a needle biopsy is performed to determine if […]