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The recognition and normalization of clinical information, such as tumormorphology mentions, is an important, but complex process consisting ofmultiple subtasks. In this paper, we describe our system for the CANTEMISTshared task, which is able to extract, normalize and rank ICD codes fromSpanish electronic health records using neural sequence labeling and parsingapproaches with context-aware embeddings. Our best system achieves 85.3 F1,76.7 F1, and 77.0 MAP for the three tasks, respectively.

NLNDE at CANTEMIST: Neural Sequence Labeling and Parsing Approaches for Clinical Concept Extraction