Center for Research, Development and Evaluation of Automatic Clinical Language Processing (NLP): Scientific Articles, clinical reports, comments on social networks. HiTZ has developed prototypes for medical entity recognition, standardization (ICD, Snomed- CT), automatic notification of adverse drug reactions, analysis of the temporal evolution of diseases, etc. It has benchmarks for validation of clinical NLP tools, and deep Learning models. Provides advice and training in PLN systems development.
Digital health
Evaluation Benchmark for Entity Detection Systems (drugs, disorders and symptoms)
Evaluation Benchmark for Entity Detection Systems (drugs, disorders and symptoms)
Evaluation Benchmark for ICD and Snomed CT Standarization Systems
Evaluation Benchmark for ICD and Snomed CT Standarization Systems
Platform for extracting relations between drugs and Disease /Symptoms Platform for extracting relations between drugs and Disease /Symptoms
Platform for extracting relations between drugs and Disease /Symptoms
Software for detecting and standardization of medical entities (Snomed CT, ICD)
Software for detecting and standardization of medical entities (Snomed CT, ICD)
Training capacity with an Erasmus Mundus master in PLN Since 2000
Training capacity with an Erasmus Mundus master in PLN Since 2000
Adverse Drug Reactions detection
Evaluation benchmarks for medical entity Recognition and standardization in ICD and Snomed CT.
Automatic classification of clinical records according to the International Classification of Diseases standard
Disease prevention through early identification of likely causes of admission in future patient discharges
In development and implementation of medical language processing systems