New Tech Can Predict Breast Cancer Years in Advance

Breast cancer survivors rally in a support group.


Every two minutes, a woman is diagnosed with breast cancer. The question is, can those at high risk be identified early enough to survive?

New AI software has predicted risk equally well in both white and black women for the first time.

The current standard practice in medicine is not exactly precise. It relies on age, family history of cancer, and breast density, among other factors, to determine risk. But these factors do not always tell the whole story, leaving many women to slip through the cracks. In addition, a racial gap persists in breast cancer treatment and survival. African-American women are 42 percent more likely to die from the disease despite relatively equal rates of diagnosis.

But now those grim statistics could be changing. A team of researchers from MIT's Computer Science and Artificial Intelligence Laboratory have developed a deep learning model that can more accurately predict a patient's breast cancer risk compared to established clinical guidelines – and it has predicted risk equally well in both white and black women for the first time.

The Lowdown

Study results published in Radiology described how the AI software read mammogram images from more than 60,000 patients at Massachusetts General Hospital to identify subtle differences in breast tissue that pointed to potential risk factors, even in their earliest stages. The team accessed the patients' actual diagnoses and determined that the AI model was able to correctly place 31 percent of all cancer patients in the highest-risk category of developing breast cancer within five years of the examination, compared to just 18 percent for existing models.

"Each image has hundreds of thousands of pixels identifying something that may not necessarily be detected by the human eye," said MIT professor Regina Barzilay, one of the study's lead authors. "We all have limited visual capacities so it seems some machines trained on hundreds of thousands of images with a known outcome can capture correlations the human eye might not notice."

Barzilay, a breast cancer survivor herself, had abnormal tissue patterns on mammograms in 2012 and 2013, but wasn't diagnosed until after a 2014 image reading, illustrating the limitations of human processing alone.

MIT professor Regina Barzilay, a lead author on the new study and a breast cancer survivor herself.

(Courtesy MIT)

Next up: The MIT team is looking at training the model to detect other cancers and health risks. Barzilay recalls how a cardiologist told her during a conference that women with heart diseases had a different pattern of calcification on their mammograms, demonstrating how already existing images can be used to extract other pieces of information about a person's health status.

Integration of the AI model in standard care could help doctors better tailor screening and prevention programs based on actual instead of perceived risk. Patients who might register as higher risk by current guidelines could be identified as lower risk, helping resolve conflicting opinions about how early and how often women should receive mammograms.

Open Questions: While the results were promising, it's unknown how well the model will work on a larger scale, as the study looked at data from just one institution and used mammograms supplied by just one hospital. Some risk factor information was also unavailable for certain patients during the study, leaving researchers unable to fully compare the AI model's performance to that of the traditional standard.

One incentive to wider implementation and study, however, is the bonus that no new hardware is required to use the AI model. With other institutions now showing interest, this software could lead to earlier routine detection and treatment of breast cancer — resulting in more lives saved.

Shannon Shelton Miller
Shannon Shelton Miller is an award-winning freelance writer and journalist based in Dayton, Ohio. She has written for the New York Times, the Washington Post, USA Today, the Detroit Free Press and the Orlando Sentinel. Visit her website at
Get our top stories twice a month
Follow us on

On the left, a Hermès bag made using fine mycelium as a leather alternative, made in partnership with the biotech company MycoWorks; on right, a sheet of mycelium "leather."

Photo credit: Coppi Barbieri and MycoWorks

A natural material that looks and feels like real leather is taking the fashion world by storm. Scientists view mycelium—the vegetative part of a mushroom-producing fungus—as a planet-friendly alternative to animal hides and plastics.

Products crafted from this vegan leather are emerging, with others poised to hit the market soon. Among them are the Hermès Victoria bag, Lululemon's yoga accessories, Adidas' Stan Smith Mylo sneaker, and a Stella McCartney apparel collection.

Keep Reading Keep Reading
Susan Kreimer
Susan Kreimer is a New York-based freelance journalist who has followed the landscape of health care since the late 1990s, initially as a staff reporter for major daily newspapers. She writes about breakthrough studies, personal health, and the business of clinical practice. Raised in the Chicago area, she holds a B.A. in Journalism/Mass Communication and French from the University of Iowa and an M.S. from the Columbia University Graduate School of Journalism.

From a special food to a vaccine and gene editing, new technologies may offer solutions for cat lovers with allergies.

Photo by Pacto Visual on Unsplash

Amy Bitterman, who teaches at Rutgers Law School in Newark, gets enormous pleasure from her three mixed-breed rescue cats, Spike, Dee, and Lucy. To manage her chronically stuffy nose, three times a week she takes Allegra D, which combines the antihistamine fexofenadine with the decongestant pseudoephedrine. Amy's dog allergy is rougher--so severe that when her sister launched a business, Pet Care By Susan, from their home in Edison, New Jersey, they knew Susan would have to move elsewhere before she could board dogs. Amy has tried to visit their brother, who owns a Labrador Retriever, taking Allegra D beforehand. But she began sneezing, and then developed watery eyes and phlegm in her chest.

"It gets harder and harder to breathe," she says.

Animal lovers have long dreamed of "hypo-allergenic" cats and dogs. Although to date, there is no such thing, biotechnology is beginning to provide solutions for cat-lovers. Cats are a simpler challenge than dogs. Dog allergies involve as many as seven proteins. But up to 95 percent of people who have cat allergies--estimated at 10 to 30 percent of the population in North America and Europe--react to one protein, Fel d1. Interestingly, cats don't seem to need Fel d1. There are cats who don't produce much Fel d1 and have no known health problems.

Keep Reading Keep Reading
Temma Ehrenfeld
Temma Ehrenfeld writes about health and psychology. In a previous life, she was a reporter and editor at Newsweek and Fortune. You can see more of her work at her writing portfolio ( and contact her through her Psychology Today blog.