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Medical records store an amount of valuable information about patients, from family history that can identify possible risks for diseases, to which medications that patient takes or has already taken, which indicates the medical alterations they have had. However, this information is written in free text in the most diverse ways, which makes it difficult for other physicians to use this information and even for hospital management.
In this work, we used a set of NLP models combined with some data treatments and medical definitions to structure this information from the medical reports in portuguese and use them to extract alterations such as diabetes and arterial hypertension.

Presented by Jéssica dos Santos de Oliveira, Data Head at NeuralMed

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