Objectives: To validate the performance of Mirai, a mammography-based deep learning model, in predicting breast cancer risk over a 1-5-year period in Mexican women.
Methods: This retrospective single-center study included mammograms in Mexican women who underwent screening mammography between January 2014 and December 2016. For women with consecutive mammograms during the study period, only the initial mammogram was included.
Children are more sensitive to ionizing radiation than adults. Even though the risk is very low, exposure from radiological examinations can possibly cause them long-term side effects. Recent large epidemiological studies involving children and young adults have added evidence suggesting that even small doses of radiation, such as those from computed tomography scans, might slightly increase the risk of developing cancer later in life.
View Article and Find Full Text PDFOver the last decades, magnetic resonance imaging (MRI) has emerged as a valuable adjunct to prenatal ultrasound for evaluating fetal malformations. Several radiological societies advocate for standardised and structured reporting practices to enhance the uniformity of imaging language. Compared to narrative formats, standardised and structured reports offer enhanced content quality, minimise reader variability, have the potential to save reporting time, and streamline the communication between specialists by employing a shared lexicon.
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