Clinical Text Mining: Secondary Use of Electronic Patient Records
暫譯: 臨床文本挖掘:電子病歷的二次使用
Hercules Dalianis
- 出版商: Springer
- 出版日期: 2018-05-24
- 售價: $2,610
- 貴賓價: 9.5 折 $2,480
- 語言: 英文
- 頁數: 181
- 裝訂: Hardcover
- ISBN: 3319785028
- ISBN-13: 9783319785028
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相關分類:
Text-mining
海外代購書籍(需單獨結帳)
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相關主題
商品描述
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 for research 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.
The book provides a comprehensive overview of technical issues arising in clinical text mining, and offers a valuable guide for advanced students in health informatics, computational linguistics, and information retrieval, and for researchers entering these fields.
商品描述(中文翻譯)
這本開放存取的書籍描述了應用於電子病歷的臨床文本的自然語言處理和機器學習方法的結果。
本書分為十二章。第1至第4章討論了原始紙本病歷的歷史和背景、其目的,以及如何撰寫和結構這些病歷。這些初始章節不需要任何技術或醫學背景知識。其餘八章則更具技術性,描述了各種醫療分類和術語,如ICD診斷碼、SNOMED CT、MeSH、UMLS和ATC。第5至第10章涵蓋了自然語言處理和資訊檢索的基本工具,以及如何將它們應用於臨床文本。書中還解釋了基於規則的方法與基於機器學習的方法之間的區別,以及監督式和非監督式機器學習方法之間的區別。接下來,書中討論了使用敏感病歷進行研究的倫理問題,包括去識別化電子病歷的方法和安全存儲病歷的方式。本書的結尾章節介紹了臨床文本挖掘中的多個應用,並總結了從前幾章中學到的教訓。
本書提供了臨床文本挖掘中出現的技術問題的全面概述,並為健康資訊學、計算語言學和資訊檢索的高級學生以及進入這些領域的研究人員提供了寶貴的指導。