IMAGE: An imaging technique that takes advantage of machine learning technology allows scientists to obtain results quickly, in contrast to traditional, more expensive methods that could take weeks. view more
Credit: (Image/Courtesy of Rishi Rabat)
A research team led by USC scientists has developed a new way to identify molecular markers of breast cancer tumors, a potentially life-saving breakthrough that could lead to better treatment for millions of women.
Aided by machine learning, the researchers taught a computer to rapidly sort images of breast tumors to identify which ones had estrogen receptors, a key to determining prognosis and treatment options. That’s a big step forward from microscopes and cell biopsies in use for more than a century, according to the scientists.
The work opens a new pathway for breast cancer treatment that promises faster results for less cost for more people worldwide, said David B. Agus, professor at the Keck School of Medicine of USC and the USC Viterbi School of Engineering. He is also CEO of the Lawrence J. Ellison Institute for Transformative Medicine of USC.
The findings appear this week in Nature Partner Journals Breast Cancer.
“It’s the beginning of a revolution to use machine learning to
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