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Can AI reduce time to breast cancer diagnosis?

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A new research study from Northwestern Medicine and Google will explore whether Artificial Intelligence (AI) models can reduce the time to diagnosis for women whose mammograms show a higher likelihood of breast cancer. The trial will evaluate if investigational AI models could help by prioritizing radiologist review of mammogram images with a higher suspicion of breast cancer. Digital mammography, or X-ray imaging of the breast, is the most common method to try to catch breast cancer as early as possible, with approximately 40 million exams performed each year in the U.S. In the current system, women go to the clinic for their mammogram and then 10% to 15% of them will require an additional diagnostic workup. This can take days or even weeks and requires at least two trips to the clinic for the patient, often resulting in added worry during that period of waiting. The AI model is trained to quickly find the mammograms which need further review and prioritize these for the radiologist to review.


Study finds Google system could improve breast cancer detection

The Japan Times

CHICAGO – A Google artificial intelligence system proved as good as expert radiologists at predicting which women would develop breast cancer based on screening mammograms and showed promise at reducing errors, researchers in the United States and Britain reported. The study, published in the journal Nature on Wednesday, is the latest to show that artificial intelligence (AI) has the potential to improve the accuracy of screening for breast cancer, which affects one in eight women globally. Radiologists miss about 20 percent of breast cancers in mammograms, the American Cancer Society says, and half of all women who get the screenings over a 10-year period have a false positive result. The findings of the study, developed with Alphabet's DeepMind AI unit, which merged with Google Health in September, represent a major advance in the potential for the early detection of breast cancer, said Mozziyar Etemadi, one of its co-authors from Northwestern Medicine in Chicago. The team, which included researchers at Imperial College London and Britain's National Health Service, trained the system to identify breast cancers on tens of thousands of mammograms.


Google system could improve breast cancer detection - study

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In the United States, only one radiologist reads the results and the tests are done every one to two years. In Britain, the tests are done every three years, and each is read by two radiologists. When they disagree, a third is consulted.'SUBTLE CUES'In a separate test, the group pitted the AI system against six radiologists and found it outperformed them at accurately detecting breast cancers.Connie Lehman, chief of the breast imaging department at Harvard's Massachusetts General Hospital, said the results are in line with findings from several groups using AI to improve cancer detection in mammograms, including her own work.The notion of using computers to improve cancer diagnostics is decades old, and computer-aided detection (CAD) systems are commonplace in mammography clinics, yet CAD programs have not improved performance in clinical practice.The issue, Lehman said, is that current CAD programs were trained to identify things human radiologists can see, whereas with AI, computers learn to spot cancers based on the actual results of thousands of mammograms.This has the potential to "exceed human capacity to identify subtle cues that the human eye and brain aren't able to perceive," Lehman added.Although computers have not been "super helpful" so far, "what we've shown at least in tens of thousands of mammograms is the tool can actually make a very well-informed decision," Etemadi said.The study has some limitations. Most of the tests were done using the same type of imaging equipment, and the U.S. group contained a lot of patients with confirmed breast cancers.Crucially, the team has yet to show the tool improves patient care, said Dr Lisa Watanabe, chief medical officer of CureMetrix, whose AI mammogram program won U.S. approval last year."AI


Study finds Google system could improve breast cancer detection - Reuters

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CHICAGO (Reuters) - A Google artificial intelligence system proved as good as expert radiologists at detecting which women had breast cancer based on screening mammograms and showed promise at reducing errors, researchers in the United States and Britain reported. The study, published in the journal Nature on Wednesday, is the latest to show that artificial intelligence (AI) has the potential to improve the accuracy of screening for breast cancer, which affects one in eight women globally. Radiologists miss about 20% of breast cancers in mammograms, the American Cancer Society says, and half of all women who get the screenings over a 10-year period have a false positive result. The findings of the study, developed with Alphabet Inc's (GOOGL.O) DeepMind AI unit, which merged with Google Health in September, represent a major advance in the potential for the early detection of breast cancer, Mozziyar Etemadi, one of its co-authors from Northwestern Medicine in Chicago, said. The team, which included researchers at Imperial College London and Britain's National Health Service, trained the system to identify breast cancers on tens of thousands of mammograms.


AI can diagnose breast cancer more accurately than a doctor can

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Artificial intelligence can diagnose breast cancer more accurately than trained doctors, a study suggests. The research on almost 30,000 women who underwent screening found a computer programme could reduce the number of cases missed by more than two thirds. Researchers said the algorithmdeveloped by Imperial College London, Northwestern University in Chicago and Google Health was a "huge advance" in early detection of cancers. Breast cancer is the most common type of cancer in the UK, affecting around one in eight women - with 55,000 diagnoses annually and 11,000 deaths. Experts said the breakthrough could save thousands of lives, by finding deadly tumours that would otherwise go undetected.