Group items tagged

"Researchers involved in a recent study trained an artificial intelligence (AI) model to diagnose type 2 diabetes in patients after six to 10 seconds of listening to their voice. Canadian medical researchers trained the machine-learning AI to recognise 14 vocal differences in the voice of someone with type 2 diabetes compared to someone without diabetes. The auditory features that the AI focussed on included slight changes in pitch and intensity, which human ears cannot distinguish. This was then paired with basic health data gathered by the researchers, such as age, sex, height and weight. Researchers believe that the AI model will drastically lower the cost for people with diabetes to be diagnosed."

"The app then measures 14 health parameters (Glucose, Protein, Urobilinogen, Calcium, Blood, Creatinine, pH, Ketone, Bilirubin, Specific Gravity, Nitrites, Leucocyte, Ascorbic Acid, Microalbumin) using routine urine analysis, provides day-to-day analytics, and, importantly, enables regular monitoring for early warning markers for more than 25 medical conditions, including complications of diabetes, pregnancy, kidney disease, and urinary tract infections. The whole idea is to spot risks early, and to address big problems before they become too big. This is important both for the home user, as well for the beneficiary of the low-cost clinic in the developing world. "

This discrepancy has made it relatively easy to connect an anonymous line of data to a specific person: if a private detective is searching for someone in New York City and knows the subject is male, is 30 to 35 years old and has diabetes, the sleuth would not be able to deduce the man's name-but could likely do so quite easily if he or she also knows the target's birthday, number of children, zip code, employer and car model.