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AI system outperforms experts in spotting breast cancer

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An artificial intelligence program has been developed that is better at spotting breast cancer in mammograms than expert radiologists. The AI outperformed the specialists by detecting cancers that the radiologists missed in the images, while ignoring features they falsely flagged as possible tumours. If the program proves its worth in clinical trials, the software, developed by Google Health, could make breast screening more effective and ease the burden on health services such as the NHS where radiologists are in short supply. "This is a great demonstration of how these technologies can enable and augment the human expert," said Dominic King, the UK lead at Google Health. "The AI system is saying'I think there may be an issue here, do you want to check?'"


Artificial intelligence used in clinical practice to measure breast density

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OAK BROOK, Ill. - An artificial intelligence (AI) algorithm measures breast density at the level of an experienced mammographer, according to a new study published in the journal Radiology. The researchers said the study, the result of a collaboration between breast imagers and AI experts, represents a groundbreaking implementation of AI into routine clinical practice. Breast density can mask cancers on mammography and is an independent risk factor for the disease. The masking effect and cancer risk are significant enough that many states have laws mandating women be notified if they have mammographically dense breasts. Despite its importance, breast density assessment is an imperfect science, and research has shown much discrepancy among radiologists in making density determinations.


UCSF Launches Artificial Intelligence Center to Advance Medical Imaging

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UC San Francisco is launching a new center to accelerate the application of artificial intelligence (AI) technology to radiology, leveraging advanced computational techniques and industry collaborations to improve patient diagnoses and care. The Center for Intelligent Imaging, or ci2, will develop and apply AI to devise powerful new ways to look inside the body and to evaluate health and disease. Investigators in ci2 will team with Santa Clara, Calif.-based NVIDIA Corp., an industry leader in AI computing, to build infrastructure and tools focused on enabling the translation of AI into clinical practice. "Artificial intelligence represents the next frontier for diagnostic medicine," said Christopher Hess, MD, PhD, chair of the UCSF Department of Radiology and Biomedical Imaging. "It is poised to revolutionize the way in which imaging is performed, interpreted and used to direct care for patients. "The Center for Intelligent Imaging will serve as a hub for the multidisciplinary ...


UCSF Launches Artificial Intelligence Center to Advance Medical Imaging

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This post was authored by Elizabeth Fernandez, senior public information representative with UCSF News. "Intelligent Imaging" Hub will harness computational tools in medical imaging to improve patient care. UC San Francisco is launching a new center to accelerate the application of artificial intelligence (AI) technology to radiology, leveraging advanced computational techniques and industry collaborations to improve patient diagnoses and care. The Center for Intelligent Imaging, or ci2, will develop and apply AI to devise powerful new ways to look inside the body and to evaluate health and disease. Investigators in ci2 will team with Santa Clara, California-based NVIDIA Corp., an industry leader in AI computing, to build infrastructure and tools focused on enabling the translation of AI into clinical practice.


Using AI to predict breast cancer and personalize care

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Despite major advances in genetics and modern imaging, the diagnosis catches most breast cancer patients by surprise. For some, it comes too late. Later diagnosis means aggressive treatments, uncertain outcomes, and more medical expenses. As a result, identifying patients has been a central pillar of breast cancer research and effective early detection. With that in mind, a team from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and Massachusetts General Hospital (MGH) has created a new deep-learning model that can predict from a mammogram if a patient is likely to develop breast cancer as much as five years in the future.