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Clinical OMICs

Koch Institute fellow Dr. Rameen Shakur and his colleagues have developed a new computer tool that could allow doctors to personalize treatments for patients with inherited heart disease. “In areas such as cardiology and oncology, where large amounts of clinical and genetic data need to be analyzed, adopting a computer-based approach…can make diagnosis, outcome prediction and treatment more effective and efficient,” writes Helen Albert for Clinical OMICs.

The Washington Post

Professor Martin Bazant and Professor John Bush have developed a new safety guideline to limit the risk of airborne Covid-19 transmission in different indoor settings. “For airborne transmission, social distancing in indoor spaces is not enough, and may provide a false sense of security,” says Bazant. “Efficient mask use is the most effective safety measure, followed by room ventilation, then filtration,” adds Bush.

CNN

CNN reporter Maggie Fox writes that MIT researchers have developed a new formula for calculating the risk of airborne Covid-19 transmission in indoor settings. "To minimize risk of infection, one should avoid spending extended periods in highly populated areas. One is safer in rooms with large volume and high ventilation rates," write Profs. Martin Bazant and John Bush.
 

Stat

A team from MIT has been named a co-winner of this year’s STAT Madness, a bracket-style competition for biomedical research. The team, led by visiting scientist Junwei Li and Prof. Gio Traverso, “developed a solution that, once inside the small intestine, undergoes a reaction and coats it with a temporary adhesive,” which could be used “to make drug delivery more efficient," reports Rebecca Sohn for STAT.

Forbes

Forbes contributor Jack Kelly spotlights Ginger, an MIT startup that has created “a smartphone-based technology app helps identify patterns of anxiety, stress and depression.”

US News & World Report

Researchers from MIT have developed a new kind of surgery that could offer amputees better control of their muscles and prosthetic limbs after surgery, reports Cara Murez for U.S. News & World Report. “In this new type of surgery — called agonist-antagonist myoneural interface, or AMI — surgeons reconnect those muscle pairs so they retain the push-pull relationship they've always had and improve sensory feedback,” writes Murez.

Mashable

Mashable spotlights how MIT researchers have developed a new type of amputation surgery that could “help amputees better control their residual muscles and sense where their ‘phantom limb’ is in space.” 

The Boston Globe

Postdoc Shriya Srinivasan has devised a new way to perform amputation surgery that would reconnect dangling nerves to the skin and help restore a patient’s sense of touch, reports Anissa Gardizy for The Boston Globe. “I would hope that in the next 10 years, people are offered the ability to have these advanced techniques incorporated into their initial surgery,” she said.

Economist

Research scientist Brian Subirana speaks with The Economist’s Babbage podcast about his work developing a new AI system that could be used to help diagnose people asymptomatic Covid-19.

Boston 25 News

Prof. James Collins speaks with Boston 25 reporter Julianne Lima about the growing issue of antibiotic resistant bacteria and his work using AI to identify new antibiotics. Collins explains that a new platform he developed with Prof. Regina Barzilay uncovered “a host of new antibiotics including one that we call halicin that has remarkable activity against multi drug-resistant pathogens.”

BBC News

A new algorithm developed by MIT researchers could be used to help detect people with Covid-19 by listening to the sound of their coughs, reports Zoe Kleinman for BBC News. “In tests, it achieved a 98.5% success rate among people who had received an official positive coronavirus test result, rising to 100% in those who had no other symptoms,” writes Kleinman.

Mashable

Mashable reporter Rachel Kraus writes that a new system developed by MIT researchers could be used to help identify patients with Covid-19. Kraus writes that the algorithm can “differentiate the forced coughs of asymptomatic people who have Covid from those of healthy people.”

Gizmodo

A new took developed by MIT researchers uses neural networks to help identify Covid-19, reports Alyse Stanley for Gizmodo. The model “can detect the subtle changes in a person’s cough that indicate whether they’re infected, even if they don’t have any other symptoms,” Stanley explains.

TechCrunch

TechCrunch reporter Devin Coldewey writes that MIT researchers have built a new AI model that can help detect Covid-19 by listening to the sound of a person’s cough. “The tool is detecting features that allow it to discriminate the subjects that have COVID from the ones that don’t,” explains Brian Subirana, a research scientist in MIT’s Auto-ID Laboratory.

CBS Boston

MIT researchers have developed a new AI model that could help identify people with asymptomatic Covid-19 based on the sound of their cough, reports CBS Boston. The researchers hope that in the future the model could be used to help create an app that serves as a “noninvasive prescreening tool to figure out who is likely to have the coronavirus.”