HP osasungintzan

Automatic Classification of Medical Records with Multi-label Classifiers and Similarity Match Coders

Gehiago irakurriAutomatic Classification of Medical Records with Multi-label Classifiers and Similarity Match Coders -ri buruz

Extreme multi-label ICD classification: sensitivity to hospital service and time

Gehiago irakurriExtreme multi-label ICD classification: sensitivity to hospital service and time -ri buruz

Extracting Cause of Death from Verbal Autopsy with Deep Learning interpretable methods

Gehiago irakurriExtracting Cause of Death from Verbal Autopsy with Deep Learning interpretable methods -ri buruz

Neural negated entity recognition in Spanish electronic health records

Gehiago irakurriNeural negated entity recognition in Spanish electronic health records -ri buruz

Adverse Drug Reaction extraction on Electronic Health Records written in Spanish

Gehiago irakurriAdverse Drug Reaction extraction on Electronic Health Records written in Spanish -ri buruz

Recent advances in Swedish and Spanish medical entity recognition in clinical texts using deep neural approaches

https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-0...

Gehiago irakurriRecent advances in Swedish and Spanish medical entity recognition in clinical texts using deep neural approaches -ri buruz

Boosting ICD multi-label classification of health records with contextual embeddings and label-granularity

https://www.sciencedirect.com/science/article/pii/S0169260719311745

Gehiago irakurriBoosting ICD multi-label classification of health records with contextual embeddings and label-granularity -ri buruz

Adverse Drug Reaction extraction on Electronic Health Records written in Spanish.

Gehiago irakurriAdverse Drug Reaction extraction on Electronic Health Records written in Spanish. -ri buruz

IxaMed at PharmacoNER Challenge 2019

Gehiago irakurriIxaMed at PharmacoNER Challenge 2019 -ri buruz

IxaMed at eHealth-KD Challenge 2019: Using Different Paradigms to Solve Clinical Relation Extraction

Gehiago irakurriIxaMed at eHealth-KD Challenge 2019: Using Different Paradigms to Solve Clinical Relation Extraction -ri buruz

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