Researchers from the University of Massachusetts Amherst have created an AI that listens for coughing and sneezing sounds to estimate what percentage of people in a public space have a respiratory illness. The device, called FluSense, was initially tested over an eight month period in four clinic waiting rooms on the university's campus. In addition to recording'non-speech' audio samples, FluSense is also equipped with a thermal camera to scan for people with elevated temperatures. According to its co-creator, Tauhidur Rahman, the device isn't meant to single out individual cases of illness but capture trends at the population level to see if something is developing that may not yet have been picked up in medical testing. 'I thought if we could capture coughing or sneezing sounds from public spaces where a lot of people naturally congregate, we could utilize this information as a new source of data for predicting epidemiologic trends,' he told UMass Amherst's news blog.

A team of researchers from the University of Central Florida have developed an artificial intelligence system to detect cancerous tumors normally missed by radiologists, the university stated in a blog post. The team has trained a computer to identify minute particles of lung cancer in CT scans, which are otherwise difficult for radiologists to pinpoint. The researchers claim that the system is about 95% accurate at identifying cancer versus 65% by humans, the blog added. The AI uses an algorithm similar to facial-recognition software that scans thousands of faces to identify and match a particular pattern. "We used the brain as a model to create our system. You know how connections between neurons in the brain strengthen during development and learn? We used that blueprint, if you will, to help our system understand how to look for patterns in the CT scans and teach itself how to find these tiny tumors," said Rodney LaLonde, a doctoral candidate, in the blog post.