Background: The IDENTIFY study developed a model to predict urinary tract cancer using patient characteristics from a large multicentre, international cohort of patients referred with haematuria. In addition to calculating an individual's cancer risk, it proposes thresholds to stratify them into very-low-risk (<1%), low-risk (1-<5%), intermediate-risk (5-<20%), and high-risk (≥20%) groups.
Objective: To externally validate the IDENTIFY haematuria risk calculator and compare traditional regression with machine learning algorithms.
Adenomyoepithelioma (AME) of the breast is a rare tumor that can be benign or malignant and has varied morphological features. We report a case of a 62-year-old female with a history of right breast cancer who presented with abnormal screening mammography. The detection, presentation, and varied imaging characteristics of AMEs are discussed.
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