UCLA Jonsson Comprehensive Cancer Center : Latest News

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UCLA researchers have developed an artificial intelligence system that could help pathologists read biopsies more accurately and to better detect and diagnose breast cancer. The new system, described in a study published today in JAMA Network Open, helps interpret medical images used to diagnose breast cancer that can be difficult for the human eye to classify, and it does so nearly as accurately or better as experienced pathologists. "It is critical to get a correct diagnosis from the beginning so that we can guide patients to the most effective treatments," said Dr. Joann Elmore, the study's senior author and a professor of medicine at the David Geffen School of Medicine at UCLA. A 2015 study led by Elmore found that pathologists often disagree on the interpretation of breast biopsies, which are performed on millions of women each year. That earlier research revealed that diagnostic errors occurred in about one out of every six women who had ductal carcinoma in situ (a noninvasive type of breast cancer), and that incorrect diagnoses were given in about half of the biopsy cases of breast atypia (abnormal cells that are associated with a higher risk for breast cancer).


Artificial intelligence could yield more accurate breast cancer diagnoses: System can interpret images that are challenging for doctors to classify

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The new system, described in a study published in JAMA Network Open, helps interpret medical images used to diagnose breast cancer that can be difficult for the human eye to classify, and it does so nearly as accurately or better as experienced pathologists. "It is critical to get a correct diagnosis from the beginning so that we can guide patients to the most effective treatments," said Dr. Joann Elmore, the study's senior author and a professor of medicine at the David Geffen School of Medicine at UCLA. A 2015 study led by Elmore found that pathologists often disagree on the interpretation of breast biopsies, which are performed on millions of women each year. That earlier research revealed that diagnostic errors occurred in about one out of every six women who had ductal carcinoma in situ (a noninvasive type of breast cancer), and that incorrect diagnoses were given in about half of the biopsy cases of breast atypia (abnormal cells that are associated with a higher risk for breast cancer). "Medical images of breast biopsies contain a great deal of complex data and interpreting them can be very subjective," said Elmore, who is also a researcher at the UCLA Jonsson Comprehensive Cancer Center.


Artificial intelligence could yield more accurate breast cancer diagnoses 7wData

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Researchers at University of Washington and University of California, Los Angeles, have developed an artificial intelligence system that could help pathologists read biopsies more accurately, and lead to better detection and diagnosis of breast cancer. Doctors examine images of breast tissue biopsies to diagnose breast cancer. But the differences between cancerous and benign images can be difficult for the human eye to classify. This new algorithm helps interpret them -- and it does so nearly as accurately or better than an experienced pathologist, depending on the task. The research team published its results Aug. 9 in the journal JAMA Network Open.


New AI Delivers More Accurate Breast Cancer Diagnoses Than Human Doctors

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"It is critical to get a correct diagnosis from the beginning so that we can guide patients to the most effective treatments," said Dr. Joann Elmore, the study's senior author and a professor of medicine at the David Geffen School of Medicine at UCLA. Why would there be a need for such a study? Well, because, according to a 2015 study led by Elmore, pathologists often disagree on the outcome of breast biopsies. Furthermore, research has also found that diagnostic errors occurred in about one out of every six women who had ductal carcinoma in situ (DCIS) and incorrect diagnoses were given in about half of the biopsy cases of breast atypia. These are quite some significant errors.


AI more accurate than docs in challenging breast cancer diagnoses

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An artificial intelligence system has outperformed pathologists in differentiating atypia from ductal carcinoma in situ--considered to be the greatest challenge in breast cancer diagnosis. In a diagnostic study involving 240 breast biopsy images, the performance of the AI system was compared with independent interpretations from 87 practicing U.S. pathologists. "In the classification tasks of atypia and DCIS versus benign and DCIS versus atypia, the associated sensitivities are higher than the sensitivity of the practicing pathologists who independently interpreted the same specimens," according to the study's authors. Results of the study, supported by the National Cancer Institute of the National Institutes of Health, were published last week in JAMA Network Open. "Medical images of breast biopsies contain a great deal of complex data, and interpreting them can be very subjective," says senior author Joann Elmore, professor of medicine at UCLA's David Geffen School of Medicine and a researcher at the UCLA Jonsson Comprehensive Cancer Center.