Health care

Writing for The Boston Globe, Prof. Linda Griffith underscores the pressing need to invest in studying women’s health and menstruation science. “These were the attitudes society had about breast cancer decades ago; we didn’t talk about it. But then we finally focused on the science, and overcame the squeamishness about mentioning ‘breasts’ by creating a technical language that could be spoken without hesitation by anyone,” writes Griffith. “We need a similar scientific push for menstruation science, and a comfort level with the language that goes with it. It’s time.”

Jamie Karraker BS ’12 MS ’13 co-founded Alto Pharmacy – a full-service, online pharmacy that aims to create a transparent, straightforward and user-friendly experience, reports Erika Fry for Fortune. “All patients need to do after seeing their doctor is interface with the app (or via text) and pick up the prescription from their front door,” writes Fry.

Researchers at MIT are working on a system that can track the development of Parkinson’s disease by monitoring a person’s gait speed, reports Kyle Wiggers and Devin Coldewey for TechCrunch. “The MIT Parkinson’s-tracking effort aims to help clinicians overcome challenges in treating the estimated 10 million people afflicted by the disease globally,” writes Wiggers and Coldewey.

Forbes reporter Marija Butkovic spotlights Alicia Chong Rodriguez MS ’18, Founder and CEO of Bloomer Tech, for her work in building a cardiovascular disease and stroke database that can generate non-invasive digital biomarkers. “We envision a world where the future of AI in healthcare performs the best it can in women,” says Chong Rodriguez. “We also have created a digital biomarker pipeline where our digital biomarkers can explain, influence, and even improve health outcomes for women.”

MIT researchers have developed a new in-home device that can help monitor Parkinson’s patients by tracking their gait, reports Hiawatha Bray for The Boston Globe. “We know very little about the brain and its diseases,” says Professor Dina Katabi. “My goal is to develop non-invasive tools that provide new insights about the functioning of the brain and its diseases.”

Popular Science reporter Philip Kiefer writes that MIT researchers have developed an in-home device that could be used to track the progression of symptoms in Parkinson’s patients. “We can’t really ask patients to come to the clinic every day or every week,” explains graduate student Yingcheng Liu. “This technology gives us the possibility to continuously monitor patients, and provide more objective assessments.”

Lindsay Androski ’98, a full-term member of the MIT Corporation, writes an opinion piece for The Los Angeles Times about the how the lack of diversity in healthcare negatively impacts women and people of color. “The people in charge of funding healthcare research and development ultimately shape which conditions will be treated and cured,” writes Androski. “Every day the status quo continues means more suffering, mainly for people who aren’t white men.”

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.”

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.