It is important for radiologists to know in advance if a patient has an implant, since MR-scanning is incompatible with some implants. At present, the unbiased process to ascertain whether a patient could be at risk is manual and not entirely reliable. We argue that this process can be enhanced and accelerated using AI-based clinical text-mining. We therefore investigated the automatic discovery of medical implant terms in electronic-medical-records (EMRs) written in Swedish using an AI-based text mining algorithm called BERT. BERT is a state-of-the-art language model trained using a deep learning algorithm based on transformers. Results are promising.
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