Washington Post reporter Pranshu Verma writes about how Prof. Dina Katabi and her colleagues developed a new AI tool that could be used to help detect early signs of Parkinson’s by analyzing a patient’s breathing patterns. For diseases like Parkinson’s “one of the biggest challenges is that we need to get to [it] very early on, before the damage has mostly happened in the brain,” said Katabi. “So being able to detect Parkinson’s early is essential.”
Prof. Hari Balakrishnan speaks with Forbes contributor Stuart Anderson about his decision to leave India to pursue a PhD in computer science in the U.S., his love for teaching students as a professor at MIT and his work co-founding Cambridge Mobile Telematics, a software company that utilizes technology to make roads safer. “Immigration and immigrants make the United States stronger,” said Balakrishnan. “Immigration is the biggest strength that we have. We need to be able to attract and retain talent, no matter where people come from.”
MIT researchers have developed a new hardware that offers faster computation for artificial intelligence with less energy, reports Kyle Wiggers for TechCrunch. “The researchers’ processor uses ‘protonic programmable resistors’ arranged in an array to ‘learn’ skills” explains Wiggers.
Forbes contributor Jennifer Kite-Powell spotlights how MIT researchers created a new AI system that analyzes radio waves bouncing off a person while they sleep to monitor breathing patterns and help identify Parkinson’s disease. “The device can also measure how bad the disease has become and could be used to track Parkinson's progression over time,” writes Kite-Powell.
A new tool for diagnosing Parkinson’s disease developed by MIT researchers uses an AI system to monitor a person’s breathing patterns during sleep, reports Hiawatha Bray for The Boston Globe. “The system is capable of detecting the chest movements of a sleeping person, even if they’re under a blanket or lying on their side,” writes Bray. “It uses software to filter out all other extraneous information, until only the breathing data remains. Using it for just one night provides enough data for a diagnosis.”
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.
Computer science lecturer Iddo Drori and his team have developed an artificial intelligence algorithm that can solve college-level math problems at a human level, reports Susan D’Agostino for Inside Higher Ed. “The model can also explain the solutions and generate new problems that students found indistinguishable from human-generated problems,” reports D’Agostino.
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.”
Mark Lee MS ’94 spoke with Forbes reporter Karen Walker about the success of Splashtop, a company he co-founded that is developing cloud-based software that allows secure and remote access and support.
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.”