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De-identifying free text of Japanese electronic health records.

Journal of biomedical semantics | 2020

Recently, more electronic data sources are becoming available in the healthcare domain. Electronic health records (EHRs), with their vast amounts of potentially available data, can greatly improve healthcare. Although EHR de-identification is necessary to protect personal information, automatic de-identification of Japanese language EHRs has not been studied sufficiently. This study was conducted to raise de-identification performance for Japanese EHRs through classic machine learning, deep learning, and rule-based methods, depending on the dataset.

Pubmed ID: 32958039 RIS Download

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Wikipedia (tool)

RRID:SCR_004897

Wikipedia is a free, web-based, collaborative, multilingual encyclopedia project supported by the non-profit Wikimedia Foundation. Its 19 million articles (over 3.6 million in English) have been written collaboratively by volunteers around the world, and almost all of its articles can be edited by anyone with access to the site. As of July 2011, there were editions of Wikipedia in 282 languages. Wikipedia was launched in 2001 by Jimmy Wales and Larry Sanger and has become the largest and most popular general reference work on the Internet, ranking around seventh among all websites on Alexa and having 365 million readers. The name Wikipedia was coined by Larry Sanger and is a combination of wiki (a technology for creating collaborative websites, from the Hawaiian word wiki, meaning quick) and encyclopedia. Wikipedia''s departure from the expert-driven style of encyclopedia building and the large presence of unacademic content has been noted several times. Some have noted the importance of Wikipedia not only as an encyclopedic reference but also as a frequently updated news resource because of how quickly articles about recent events appear. Although the policies of Wikipedia strongly espouse verifiability and a neutral point of view, critics of Wikipedia accuse it of systemic bias and inconsistencies (including undue weight given to popular culture), and allege that it favors consensus over credentials in its editorial processes. Its reliability and accuracy are also targeted. A 2005 investigation in Nature showed that the science articles they compared came close to the level of accuracy of Encyclopedia Britannica and had a similar rate of serious errors.

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word2vec (tool)

RRID:SCR_014776

Software tool which provides implementation of the continuous bag-of-words and skip-gram architectures for computing vector representations of words. These representations can be used in many natural language processing applications and for further research. It takes a text corpus as input and produces the word vectors as output. It first constructs a vocabulary from the training text data and then learns vector representation of words. The resulting word vector file can be used as features in natural language processing and machine learning applications.

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