“The analogy I like to use is that of a blood pressure test,” explained Dr. Thomas Sawyer, chief operating officer at Cognetivity, a healthcare startup building an AI-powered test to detect the early signs of dementia.
AirShepherd and University of Southern California doctoral student Elizabeth Bondi is helping wildlife rangers stop poaching. But her team is faced with a challenge common in the data science and machine learning space: accurate labeling.
Real-time data insight isn’t just fueling race car performance—it’s pushing the boundaries of modern medicine.
When construction excavation goes deep on the University of Illinois Chicago campus, a team of data scientists, mapmakers, and engineers show up to look into the hole so regularly that they have their own hardhats and safety gear.
Text therapy and virtual clinicians are becoming more prevalent, delivering treatment in new, easier-to-access ways.
Machine intelligence is essential for success in the digital future. According to a 2017 study by management consultancy Bain, the IIoT market will generate approximately $85 billion annually by 2020.
Named CyclePhilly, the app lets cyclists voluntarily record their bike trips to help local planners and agencies understand bicycle trends, routes, and trip purposes, so they can improve bicycle facilities and connect the region’s trail network.