Certain implants are imperative to detect be-fore MRI scans. However, implant terms, like‘pacemaker’ or ‘stent’, are sparse and difficultto identify in noisy and hastily written elec-tronic medical records (EMRs). In this pa-per, we explore how to discover implant termsin Swedish EMRs with an unsupervised ap-proach.To this purpose, we use BERT, astate-of-the-art deep learning algorithm, andfine-tune a model built on pre-trained SwedishBERT. We observe that BERT discovers asolid proportion of indicative implant terms.