Category: AI

  • Phillip Alvelda: More intelligent; less artificial | ApplySci @ Stanford

    Phillip Alvelda: More intelligent; less artificial | ApplySci @ Stanford

    Phillip Alvelda discussed AI and the brain at ApplySci’s recent Wearable Tech + Digital Health + Neurotech Silicon Valley conference at Stanford: Dr. Alvelda will join us again at Wearable Tech + Digital Health + Neurotech Boston, on September 24, 2018 at the MIT Media Lab.  Other speakers include: Rudy Tanzi – Mary Lou Jepsen – George Church…

  • AI CT analysis speeds stroke identification, treatment

    AI CT analysis speeds stroke identification, treatment

    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’s Justin Sanchez on driving and reshaping biotechnology | ApplySci @ Stanford

    DARPA’s Justin Sanchez on driving and reshaping biotechnology | ApplySci @ Stanford

    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 on AI in healthcare | ApplySci @ Stanford

    Vinod Khosla + Lisa Weiner Intrator on AI in healthcare | ApplySci @ Stanford

    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

  • Phillip Alvelda:  More intelligent; less artificial | ApplySci @ Stanford

    Phillip Alvelda: More intelligent; less artificial | ApplySci @ Stanford

    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…

  • Heart attack, stroke, predicted via retinal images

    Heart attack, stroke, predicted via retinal images

    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…

  • EEG + AI assists drivers in manual and autonomous cars

    EEG + AI assists drivers in manual and autonomous cars

    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…

  • Robots visualize actions, plan, with out human instruction

    Robots visualize actions, plan, with out human instruction

    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…

  • AI detects pneumonia from chest X-rays

    AI detects pneumonia from chest X-rays

    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…

  • AI detects bowel cancer in less than 1 second in small study

    AI detects bowel cancer in less than 1 second in small study

    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…

  • Machine learning improves breast cancer detection

    Machine learning improves breast cancer detection

    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…

  • Detecting dementia with automated speech analysis

    Detecting dementia with automated speech analysis

    WinterLight Labs is developing speech analyzing algorithms to detect and monitor dementia and aphasia.  A one minute speech sample is used to determine the lexical diversity, syntactic complexity, semantic content, and articulation associated with these conditions. Clinicians currently conduct similar tests by interviewing patients and writing their impressions on paper. The company believes that their…