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A Novel COVID-19 Data Set and an Effective Deep Learning Approach for the De-Identification of Italian Medical Records.

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第一作者： Rosario,Catelli

第一单位： Institute for High Performance Computing and Networking (ICAR), National Research Council 80131 Naples Italy.

作者： Rosario,Catelli ^[1] ; Francesco,Gargiulo ^[1] ; Valentina,Casola ^[2] ; Giuseppe,De Pietro ^[1] ; Hamido,Fujita ^[3] ; Massimo,Esposito ^[1]

作者单位： Institute for High Performance Computing and Networking (ICAR), National Research Council 80131 Naples Italy. ^[1] Department of Electrical Engineering and Information TechnologiesUniversity of Naples Federico II 80125 Naples Italy. ^[2] Faculty of Information TechnologyHo Chi Minh City University of Technology (HUTECH) Ho Chi Minh 723000 Vietnam.;Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada 18014 Granada Spain.;Faculty of Software and Information ScienceIwate Prefectural University Iwate 020-0611 Japan. ^[3]

关键词 Clinical de-identification Italian language contextualized embedding deep learning named entity recognition

DOI 10.1109/ACCESS.2021.3054479

PMID 34786303

发布时间 2024-04-03

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2021年9卷

19097-19110页

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2021年9卷

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A Novel COVID-19 Data Set and an Effective Deep Learning Approach for the De-Identification of Italian Medical Records.

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A Novel COVID-19 Data Set and an Effective Deep Learning Approach for the De-Identification of Italian Medical Records.

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