5, 6 Many of these cancers are diagnosed as interval breast cancers, defined as those that emerge after a normal mammogram but before the woman's next scheduled screening.Ĭlinicians have traditionally considered risk factors such as family history as a way to assess women's risks of developing breast cancer, but about 85% of breast cancers occur in women who have no family history of breast cancer. Regular, age-based mammography screening reduces breast cancer mortality by approximately 20%, 4 but screening mammography can still miss 20 to 40% of breast cancers. This solution, now available for tomosynthesis, provides an accurate estimate of the risk of short-term breast cancer, which is truly personalized for each woman. In addition, the new version of ProFound AI Risk will also be available for demonstration at the iCAD booth at JFR. "At C.S.E., we have been using ProFound AI for 2D Mammography and DBT for several years, during which we have seen iCAD's constant commitment to improve performance in terms of both sensitivity and specificity as new versions are released." Centre Imagerie Médicale Numérique, Paris, France. "When breast cancer is diagnosed early, survival after treatment is excellent, over 90% in some countries, 2" according to Patrick Toubiana, MD, Radiologist, President and Co-Founder at the C.S.E.
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Designed for seamless integration in clinical workflow, ProFound AI results can be flexibly integrated into leading MIS/RIS, and PACS software products. Both scores are designed to assist with clinical decision making Case Scores may also be used to prioritize the reading worklist. Each case also includes a Case Score, which indicates the algorithm's confidence level for the case matching malignant cases within the ProFound AI database. Each identified region includes a Certainty of Finding score, which indicates its match to lesions within the growing ProFound AI enriched database.
Suspicious appearing structures such as densities (masses, architectural distortions, and asymmetries) and calcification clusters are identified via a contoured line. 1 The advanced deep-learning software uses advanced neural network image processing and pattern recognition to analyze mammography images for potential cancers. "By using this leading-edge technology, both general and breast radiologists can potentially improve their accuracy and performance, which may in turn have a positive impact on women and the healthcare system overall."The latest generation of ProFound AI for 2D Mammography outperforms the previous product version, offering standalone performance improvements of up to 4% increased sensitivity, up to 10% improved specificity and up to 40% faster processing. "The European launch of our third generation of ProFound AI for 2D Mammography demonstrates iCAD's steadfast commitment to improving breast cancer detection for all women worldwide," said Stacey Stevens, President of iCAD, Inc.
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