A Novel COVID-19 Data Set and an Effective Deep Learning Approach for the De-Identification of Italian Medical Records-Reference-Cited by-同舟云学术

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

Published:2021 Issue: Volume:9 Page:19097-19110
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Catelli Rosario^ORCID,Gargiulo Francesco^ORCID,Casola Valentina,De Pietro Giuseppe,Fujita Hamido,Esposito Massimo^ORCID

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9312710/09335570.pdf?arnumber=9335570

Cited by 20 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. De-identification of clinical free text using natural language processing: A systematic review of current approaches;Artificial Intelligence in Medicine;2024-05

2. Automatic de-identification of French electronic health records: a cost-effective approach exploiting distant supervision and deep learning models;BMC Medical Informatics and Decision Making;2024-02-16

3. Hybrid evolutionary intelligent network for sentiment analysis using Twitter data during COVID‐19 pandemic;Expert Systems;2023-10-30

4. Automatic Deidentification of French Electronic Health Records: A Cost-Effective Approach Exploiting Distant Supervision and Deep Learning Models;2023-09-12

5. AGORA: An intelligent system for the anonymization, information extraction and automatic mapping of sensitive documents;Applied Soft Computing;2023-09

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