Exploring Medical Records with Machine Learning and Natural Language Processing

We will present an ongoing project at Priberam that covers aspects that go from the definition of ontologies, corpus gathering and annotation criteria to the concrete annotation task, and finally the development of an engine that automatically extracts, labels and enables the exploration of textual data obtained from medical records. We will report on the resulting nested named-entity recognizer based on stack-LSTMs that achieved state-of-the-art results in standard evaluation datasets.