Electronic Resource

Clinical Text Mining : Secondary Use of Electronic Patient Records

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This open access book describes the results of natural language processing and machine learning methods applied to clinical text from electronic patient records.


It is divided into twelve chapters. Chapters 1-4 discuss the history and background of the original paper-based patient records, their purpose, and how they are written and structured. These initial chapters do not require any technical or medical background knowledge. The remaining eight chapters are more technical in nature and describe various medical classifications and terminologies such as ICD diagnosis codes, SNOMED CT, MeSH, UMLS, and ATC. Chapters 5-10 cover basic tools for natural language processing and information retrieval, and how to apply them to clinical text. The difference between rule-based and machine learning-based methods, as well as between supervised and unsupervised machine learning methods, are also explained. Next, ethical concerns regarding the use of sensitive patient records forresearch purposes are discussed, including methods for de-identifying electronic patient records and safely storing patient records. The book’s closing chapters present a number of applications in clinical text mining and summarise the lessons learned from the previous chapters.

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Availability

Detail Information

Series Title

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Call Number

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Publisher

Cham : Springer Cham., 2018

Collation

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Language

ISBN/ISSN

9783319785035

Classification

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Content Type

text

Media Type

computer

Carrier Type

online resource

Edition

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Subject(s)

Information Storage and Retrieval

Specific Detail Info

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Statement of Responsibility

Hercules Dalianis

Other Information

Cataloger

Siti Muawanah

Source

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Validator

Maya

Digital Object Identifier (DOI)

https://link.springer.com/book/10.1007/978-3-319-78503-5

Journal Volume

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Journal Issue

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Subtitle

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Parallel Title

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Other version/related

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