Tel-Aviv based start-up Aidoc, a leading provider of Artificial Intelligence solutions for radiologists, received US Food and Drug Administration (FDA) clearance for its AI solution that spots strokes (Large-Vessel Occlusion) in the brain during head CTA scans.An LVO is the blockage of vessels in the brain, and according to Ariella Shoham, Aidoc's vice president of marketing, the AI technology "uses deep learning to automatically look at every head CT before a patient has even left the imaging room. "It investigates the images to see if they show blocked blood vessels in the brain or bleeding (intracranial hemorrhages)," she explained. "If one of these time-critical conditions is found, Aidoc re-prioritizes the worklists of radiologists so that the urgent scan is looked at immediately and the patient can be treated quickly."Shoham said that Aidoc already received FDA clearances to identify and flag pulmonary embolism (blockages in the lungs) and cervical spine fractures (broken neck). "Other Aidoc solutions currently in clinical testing include identifying air in the abdomen," she continued. "Altogether, Aidoc is targeting the most common critical life-threatening conditions that make up 80% of all urgent cases on CT scans.
A person receives a test for diabetes during Care Harbor LA free medical clinic in Los Angeles, California September 11, 2014. DreaMed Diabetes, the Petah Tikva-based developer of personalized diabetes management solutions, has received US Food and Drug Administration (FDA) clearance for its artificial intelligence-powered insulin recommendations technology. The company's AI-based insulin dosing decision-support software, DreaMed Advisor Pro, aims to assist people with Type 1 diabetes (T1D) using insulin-pump therapy with continuous glucose sensors or blood glucose meters.
Developing a new drug can cost billions of dollars and take a dozen or more years to bring to market. Two Israeli researchers have applied artificial intelligence (AI) and deep learning to shave time and money off the drug-discovery process. Instead of searching for the appropriate molecules to use in a new medicine, as is done today, they enabled a computer to make smart predictions without human guidance. Shahar Harel and Kira Radinsky at the Technion-Israel Institute of Technology fed into their computer system hundreds of thousands of known molecules as well as the chemical composition of all FDA-approved drugs up until 1950. Aided by AI, the computer came up with new potential molecules by making sometimes unexpected correlations from within this massive sample.