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.”
Broad Institute postdoctoral associate Joshua Weinstein has developed a DNA microscope that allows researchers to investigate the locations and identity of DNA molecules, reports Sharon Begley for STAT. “Weinstein has so far used it to image human cancer cell lines and plans to apply the technology to tumors and the immune cells that infiltrate them,” writes Begley, “which might one day guide immunotherapy.”
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.”
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.
MIT researchers have developed tiny robots powered by magnetic fields that can be used to bring drugs nanoparticles from the bloodstream into a tumor or disease site in the human body, reports the Xinhua news agency.
Prof. Regina Barzilay speaks with NPR reporter Richard Harris about her work developing AI systems aimed at improving identification of breast cancer in mammograms, inspired by her experience with the disease. “At every point of my treatment, there would be some point of uncertainty, and I would say, 'Gosh, I wish we had the technology to solve it,’” says Barzilay.
Xinhua reports that MIT researchers have “discovered that lung tumors could hijack bacteria within the lung to promote their own survival.” As Tyler Jacks, director of the Koch Institute and the paper’s senior author explains, this research "opens up multiple potential avenues toward lung cancer interception and treatment.”
Boston Globe reporter Jessie Scanlon spotlights Prof. Regina Barzilay’s work developing machine learning systems that can identify patients at risk of developing breast cancer. Barzilay is creating “software that aims to teach a computer to analyze mammogram images more effectively than the human eye can and to catch signs of cancer in its earliest phases.”
MIT researchers have developed a new technique to measure cancer cells that provides insight into how certain cells respond to treatment, reports the Xinhua news agency. The findings could be used to help develop new drug targets, making current treatments more effective.