  Medical reports are an essential medium in recording a patient's condition
throughout a clinical trial. They contain valuable information that can be
extracted to generate a large labeled dataset needed for the development of
clinical tools. However, the majority of medical reports are stored in an
unregularized format, and a trained human annotator (typically a doctor) must
manually assess and label each case, resulting in an expensive and time
consuming procedure. In this work, we present a framework for developing a
multilingual breast MRI report classifier using a custom-built language
representation called LAMBR. Our proposed method overcomes practical challenges
faced in clinical settings, and we demonstrate improved performance in
extracting labels from medical reports when compared with conventional
approaches.
