Time (1/1) reports on a study published in Nature journal in which researchers from Google Health, and from universities in the U.S. and U.K., report on an AI model that reads mammograms with fewer false positives and false negatives than human experts.
Radiology Business (12/17) reports that Swedish scientists have developed a sophisticated new artificial intelligence model that may greatly improve radiologists’ ability to predict breast cancer risk when compared to traditional methods, according to a study published in Radiology.
Aunt Minnie (12/16) reports that vacuum-assisted image-guided breast biopsy can reliably predict which breast cancer patients treated with chemotherapy have responded well enough that follow-up surgery is not required to remove residual cancer, according to a presentation at the 2019 San Antonio Breast Cancer Symposium (SABCS).
UPI (12/12) reports on a study supported by the American Cancer Society and published in INCI Cancer Spectrum which reveals that black men are more likely than white men to develop hormone receptor positive, or HR+, breast cancer, even though the opposite is the case for women with the disease.
Aunt Minnie (12/10) reports on a study published in Radiology which states that full-field digital mammography (FFDM) detects breast cancer better than either analog film-screen mammography or computed radiography (CR), regardless of age, breast density, or screening round.