As an internist, Dr. Joann Elmore was taught to ask questions. Those questions led her to spend much of her career in breast cancer research where she found extensive variability among radiologists' interpretation of mammograms. "Radiology data is subjective, just like art. You're being asked to classify visual data," Elmore says. It wasn't until she was on the receiving end of a Friday night phone call alerting her to a "suspicious" skin biopsy, however, did Elmore's interest in melanoma peak.

The coronavirus may have been in Los Angeles around Christmas, before the novel coronavirus was officially identified in the United States, according to researchers from the University of California, Los Angeles, and the University of Washington. The team of researchers discovered a spike in patients with acute respiratory failure and coughs at UCLA Health hospitals and clinics around late December 2019, when they analyzed health records, according to a press release from the university. The findings published in a report in the Journal of Medical Internet Research suggest that novel coronavirus may have been surfacing in the area months before the first case was officially identified. Researchers said an increased number of patients with respiratory complaints starting in late December 2019 and continuing through February 2020 suggests SARS-CoV-2 community infections were present prior to official awareness of cases in the U.S. (iStock) The team of researchers analyzed more than 10 million UCLA Health System outpatient, emergency department and hospital facility records between Dec. 1, 2019, and Feb. 29, 2020 – months just before there was an awareness of the presence of the novel coronavirus in the United States. They discovered patients seeking treatment for coughs in the outpatient clinics "increased by over 50% and exceeded the average number of visits for the same complaint over the prior five years by more than 1,000," the study press release stated.

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).

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.

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.

WASHINGTON DC: Researchers discovered 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 in the journal'JAMA Network Open,' helped interpret medical images used to diagnose breast cancer that can be difficult for the human eye to classify, and it does so nearly as accurate 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).

"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.

You will be able to interact with John Madden's bronze bust at the Pro Football Hall of Fame. During his enshrinement speech at the Pro Football Hall of Fame in 2006, iconic Oakland Raiders coach, NFL analyst, pitchman and video game namesake John Madden, remarked that all the bronze busts commemorating Hall members in Canton, Ohio, secretly talk to each other after dark. Now, through a combination of conversational artificial intelligence, augmented reality, 3D animation and facial motion capture, fans attending the Super Bowl Experience in Atlanta next week, or who later visit the Hall in Canton, will be able to "converse" with an interactive version of Madden's bronze bust. You'll launch an app and hold an iOS or Android phone or tablet in front of Madden's actual bust, and ask your question – "Hey coach, what was it like after Super Bowl XI getting carried off the field?" or "What was it like to coach against Vince Lombardi?" The Raiders enjoyed their heyday under coach John Madden, who led the team to a 112-39-7 record from 1969-78.