Researchers from MIT are working with the Staten Island Performing Provider System to develop an algorithm that can predict who in the system is at risk for an opioid overdose, reports Maddie Bender for the Daily Beast. “In preliminary testing, Conte’s team and MIT Sloan researchers found their model was highly accurate at predicting overdoses and fatal overdoses, even with delays in the data of up to 180 days,” writes Bender.
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.”
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.”
Writing for The Hill, President L. Rafael Reif and Stephen A. Schwarzman, chairman, CEO & co-founder of Blackstone, praise the new “CHIPS and Science Act” and highlight the need for further action on the ‘Science’ part of the law. “We urge Congress to capitalize on this bipartisan momentum and appropriate the funds that the bill authorizes,” they write. The nation's "future competitiveness, prosperity and security all rely on technological leadership. To sustain its strength in the long term, the U.S. needs to invent and manufacture the next new technologies.”
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.
Alumni Carter Huffman ’14 and Mike Pappas ’14 co-founded Modulate, an artificial intelligence technology that helps differentiate between friendly banter and inappropriate outbursts in video game voice chats, reports Scott Kirsner for The Boston Globe. “Modulate highlights for a game’s human moderators the most severe violations of the game’s guidelines and allows them to decide on the consequences after they examine the situation,” writes Kirsner. “They may send the player a warning, mute them temporarily, or ban them from the game.”
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.”
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.
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.”
Principal Research Scientist Leo Anthony Celi oversaw a study which found that people of color were given significantly less supplemental oxygen than white people because of inaccuracies in pulse oximeter readings, reports Nancy Lapid for Reuters. “Nurses and doctors make the wrong decisions and end up giving less oxygen to people of color because they are fooled [by incorrect readings from pulse oximeters],” says Celi.