In an article they co-authored for STAT, Prof. Eric von Hippel and visiting scientist Harold DeMonaco suggest that patients often offer solutions for improving health care that medical professionals overlook. “In addition to fulfilling a personal need, patient-innovators are also attracted by the learning they gain from the process and from sharing their innovations with people with similar needs,” they write. “In short, it is a highly self-rewarding endeavor.”
Researchers at MIT and Brown University created an interactive data system that “could give everyone AI superpowers,” writes Darrell Etherington for TechCrunch. Known as ‘Northstar,’ the system can instantly generate machine-learning models to use with existing data sets in order to generate useful predictions, explains Etherington.
A new AI prediction model developed at MIT could detect breast cancer up to five years in advance. The researchers hope this technique “can also be used to improve detection of other diseases that have similar problems with existing risk models, with far too many gaps and lower degrees of accuracy,” writes Darrell Etherington for TechCrunch.
Researchers at MIT have “identified a molecule that can glue a cell-killing chemical to cancerous tissue,” reports Xinhua. This finding could ultimately “play a part in developing a low-toxicity cancer therapy.”
Writing for the Financial Times about how technology is advancing the field of health care, John Browne spotlights Prof. Bob Langer’s work developing new methods of delivering drugs with improved precision. Browne explains that Langer is working on “a device smaller than a grain of rice that he can inject into a tumour to test the efficacy of dozens of chemotherapy agents in parallel.”
Writing for Scientific American, Prof. Bob Langer examines how breakthroughs in biotechnology and materials science are enabling more personalized and effective treatments for patients. Langer highlights how by “engineering polymers that offer smart delivery systems, we can target specific parts of the body. This limits exposure and therefore adverse effects, offering more effective and precise treatment.”
President Emerita Susan Hockfield discusses her new book, “The Age of Living Machines,” her work as a neuroscientist, and the future of science and technology during a curated lunch conversation with HUBweek and Boston.com. Hockfield explains that a revolution spurred by the convergence of biology with engineering will lead to new technologies built by biology.
In an excerpt from her new book published in The Wall Street Journal, President Emerita Susan Hockfield explores how the convergence between biology and engineering is driving the development of new tools to tackle pressing human problems. Hockfield writes that for these world-changing technologies to be realized requires “not only funding and institutional support but, more fundamentally, a commitment to collaboration among unlikely partners.”
President Emerita Susan Hockfield speaks with Jim Braude of WGBH’s Greater Boston about her book, “The Age of Living Machines.” “We are looking at a population of over 9.7 billion by 2050,” explains Hockfield. “We are not going to get there without war or epidemics or starvation if we don’t develop technologies that will allow us to provide energy, food, water, health and health care sustainably.”
MIT researchers have found that tracking specific changes in the number of chromosomes inside prostate cancer cells might help determine whether tumors should be treated, reports Robert Preidt for HealthDay News. “Besides giving new insights into how prostate tumors form and spread, the chromosomal data might someday be employed clinically to inform risk stratification and treatment decisions,” Preidt explains.
Fast Company reporter Michael Grothaus writes that CSAIL researchers have developed a deep learning model that could predict whether a woman might develop breast cancer. The system “could accurately predict about 31% of all cancer patients in a high-risk category,” Grothaus explains, which is “significantly better than traditional ways of predicting breast cancer risks.”
WCVB-TV’s Jennifer Eagan reports that researchers from MIT and MGH have developed a deep learning model that can predict a patient’s risk of developing breast cancer in the future from a mammogram image. Prof. Regina Barzilay explains that the model “can look at lots of pixels and variations of the pixels and capture very subtle patterns.”
HealthDay News reporter Amy Norton writes that MIT researchers have developed an AI system that can help predict a woman’s risk of developing breast cancer and provide more personalized care. “If you know a woman is at high risk, maybe she can be screened more frequently, or be screened using MRI,” explains graduate student Adam Yala.
A gift from alumnus Charles Broderick will enable researchers at MIT and Harvard to investigate how cannabis effects the brain and behavior, reports Felice Freyer for The Boston Globe. Prof. John Gabrieli explains that it has been “incredibly hard” to get funding for marijuana research. “Without the philanthropic boost, it could take many years to work through all these issues,” he notes.
WBUR reporter Carey Goldberg spotlights how a gift from alumnus Charles Broderick is funding research on cannabis and its impacts on the brain. "We were saying, 'Wouldn't it be great to study this?'” says Prof. Myriam Heiman of the need to study the impacts of cannabis. "And then this gift comes along and really is enabling us to do everything we wanted to do."