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Labelling large datasets for training high-capacity neural networks is amajor obstacle to the development of deep learning-based medical imagingapplications. Here we present a transformer-based network for magneticresonance imaging (MRI) radiology report classification which automates thistask by assigning image labels on the basis of free-text expert radiologyreports. Our model's performance is comparable to that of an expertradiologist, and better than that of an expert physician, demonstrating thefeasibility of this approach. We make code available online for researchers tolabel their own MRI datasets for medical imaging applications.

Automated Labelling using an Attention model for Radiology reports of MRI scans (ALARM)