Medical Entity and Relation Extraction from Narrative Clinical Records in Italian Language
| Autor: | Maria Mercorella, Giuseppe De Pietro, Mario Ciampi, Crescenzo Diomaiuta |
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| Rok vydání: | 2017 |
| Předmět: |
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business.industry Search engine indexing UIMA computer.software_genre Pipeline (software) Relationship extraction Information extraction Unstructured medical records Medical entity recognition Medicine Narrative Italian natural language processing Artificial intelligence business Information Extraction computer Sentence Natural language processing Word (computer architecture) |
| Zdroj: | Intelligent Interactive Multimedia Systems and Services 2017 ISBN: 9783319594798 IIMSS KES Intelligent Interactive Multimedia: Systems and Services 2017, pp. 119–128, Vilamoura, Portugal, 21/06/2017, 23/06/2017 info:cnr-pdr/source/autori:Crescenzo Diomaiuta, Maria Mercorella, Mario Ciampi, Giuseppe De Pietro/congresso_nome:KES Intelligent Interactive Multimedia: Systems and Services 2017/congresso_luogo:Vilamoura, Portugal/congresso_data:21%2F06%2F2017, 23%2F06%2F2017/anno:2017/pagina_da:119/pagina_a:128/intervallo_pagine:119–128 |
| DOI: | 10.1007/978-3-319-59480-4_13 |
| Popis: | Applying Natural Language Processing techniques enables to unlock precious information contained in free text clinical reports. In this paper, we propose a system able to annotate medical entities in narrative records. Considering that existing NLP systems mainly concern entity recognition in English language, we propose an NLP pipeline to manage clinical free text in Italian. The overall architecture includes a spell checker, sentence detector, word tokenizer, part-of-speech tagger, dictionary lookup annotator, and parsing rules annotator. Essentially, it uses a rule-based approach to extract relevant concepts regarding patient's conditions, administered medications, or performed procedures, detecting their attributes, negated forms, and relations expressions. The indexing of the documents allows the user to retrieve relevant information, increasing his/her medical knowledge. |
| Databáze: | OpenAIRE |
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