Boston Globe reporter Hiawatha Bray speaks with Radio Boston host Tiziana Dearing about how MIT researchers developed an artificial intelligence model that uses a person’s breathing patterns to detect Parkinson’s Disease. The researchers “hope to continue doing this for other diseases like Alzheimer’s and potentially other neurological diseases,” says Bray.
Researchers at MIT have developed an artificial intelligence sensor that can track the progression of Parkinson’s disease in patients based on their breathing while they sleep, reports Conor Hale for Fierce Biotech. “The device emits radio waves and captures their reflection to read small changes in its immediate environment,” writes Hale. “It works like a radar, but in this case, the device senses the rise and fall of a person’s chest.”
MIT researchers have developed a new artificial intelligence system that uses a person’s breathing pattern to help detect Parkinson’s sisease, reports Susannah Sudborough for Boston.com. “The device emits radio signals, analyzes reflections off the surrounding environment, and monitors the person’s breathing patterns without any bodily contact,” writes Sudborough.
Researchers at MIT and other institutions have developed an artificial intelligence tool that can analyze changes in nighttime breathing to detect and track the progression of Parkinson’s disease, reports Casey Ross for STAT. “The AI was able to accurately flag Parkinson’s using one night of breathing data collected from a belt worn around the abdomen or from a passive monitoring system that tracks breathing using a low-power radio signal,” writes Ross.
Loh Down on Science host Sandra Tsing Loh spotlights Prof. Cathy Wu and graduate student Vindula Jayawardana and their work developing a new method for self-driving vehicles that would help minimize idling at red lights. “In their method, self-driving can be taught to minimize stops at red lights. To make this work, traffic lights and self-driving cars would have sensors. This would let them check in with each other on their surroundings,” says Loh.
MIT researchers have developed firefly-inspired robots that can emit light while flying, reports Popular Mechanics. “The robots may be able to converse with one another because of this electroluminescence and, for instance, a robot that finds survivors while on a search-and-rescue mission, within a fallen building, could use lights to alert others and request assistance.”
Prof. Andrew Lo speaks with Forbes contributor Russell Flannery about his work using finance to help lower the cost of drug development for cancer treatment and therapies. “I started thinking about how we could use finance pro-actively to lower the cost of drug development, increase success rates, and make it more attractive for investors,” says Lo. “Because that's really what the issue is: you need investors to come into the space to spend their billions of dollars in order to get these drugs developed.”
Fast Company reporter Elissaveta Brandon writes that a team of scientists from MIT and elsewhere have developed an amphibious artificial vision system inspired by the fiddler crab’s compound eye, which has an almost 360-degree field of view and can see on both land and water. “When translated into a machine,” writes Brandon, “this could mean more versatile cameras for self-driving cars and drones, both of which can become untrustworthy in the rain.”
Wired reporter Will Knight spotlights a study by researchers from MIT and other universities that finds judges are turning to Wikipedia for guidance when making legal decisions. “The researchers also found evidence that the use of Wikipedia reflects an already stretched system,” writes Knight. “The legal decisions that included Wikipedia-influenced citations were most often seen in the lower courts, which they suspect reflects how overworked the judges are.”
The MIT mini cheetah broke a speed record after learning to adapt to difficult terrain and upping its speed, reports Rienk De Beer for Popular Mechanics.
Postdoctoral researcher Murat Onen and his colleagues have created “a nanoscale resistor that transmits protons from one terminal to another,” reports Alex Wilkins for New Scientist. “The resistor uses powerful electric fields to transport protons at very high speeds without damaging or breaking the resistor itself, a problem previous solid-state proton resistors had suffered from,” explains Wilkins.
Researchers from CSAIL and elsewhere have found that Irish judges are using Wikipedia articles as a source in their rulings, reports Shane Phelan for Independent. “This work shows that Wikipedia reaches even farther than that, into high-stakes, formalized processes like legal judgments,” says research scientist Neil Thompson. “The worst outcome would be for a judge’s reliance on Wikipedia to lead them to decide a case differently than they would have if they had read either an expert secondary source or the cited precedent itself.”
Researchers from CSAIL, Cornell University, and Maynooth University have released a study concluding that judges in Ireland are utilizing Wikipedia articles to help inform their decisions, reports Colleen Hagerty for Popular Science. Based on their findings, the researchers suggest “the legal community increases its efforts to monitor and fact-check legal information posted on Wikipedia.”
Prof. Jesús del Alamo speaks with Ira Flatow of NPR’s Science Friday about the importance of the CHIPS Act and the pressing need to invest in semiconductor manufacturing in the U.S. “There is a deep connection between leading-edge manufacturing and innovation,” says del Alamo. “Whoever gets the most advanced technology first in the marketplace is going to rip off the greatest profits, and as a result is going to be able to invest into innovation at a greater level and therefore be able to move faster than their competitors.”
MIT researchers have developed a new system that enabled the mini robotic cheetah to learn to run, reports John Koetsier for Forbes. ““Traditionally, the process that people have been using [to train robots] requires you to study the actual system and manually design models,” explains Prof. Pulkit Agrawal. “This process is good, it’s well established, but it’s not very scalable. “But we are removing the human from designing the specific behaviors.”