Advances of Machine Learning for Knowledge Mining in Electronic Health Records

Language: English

Published by Taylor & Francis Ltd (Sales) Jun 2026, 2026

1032527811 / 9781032527819

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  • New
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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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Item description from seller

Neuware - The book explores the application of cutting-edge machine learning and deep learning algorithms in mining Electronic Health Records (EHR). With the aim of improving patient health management, this book explains the structure of EHR consisting of demographics, medical history, and diagnosis, with a focus on the design and representation of structured, semi-structured, and unstructured data. - Explains the design of organized, semi-structured, unstructured, and irregular time series data of electronic health records - Covers information extraction, standards for meta-data, reuse of metadata for clinical research, and organized and unstructured data - Discusses supervised and unsupervised learning in electronic health records - Describes clustering and classification techniques for organized, semi- structured, and unstructured data from electronic health records This book is an essential resource for researchers and professionals in fields like computer science, biomedical engineering, and information technology, seeking to enhance healthcare efficiency, security, and privacy through advanced data analytics and machine learning.

Seller Inventory # 9781032527819

Title
Advances of Machine Learning for Knowledge Mining in Electronic Health Records
Author
J B Shajilin Loret
Publisher
Taylor & Francis Ltd (Sales) Jun 2026
Publication year
2026
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
1032527811
ISBN 13
9781032527819
Item weight
404 grams
Dimensions
234x156x15 mm

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

Shipping rates from Germany to U.S.A.

Item5 to 7 business days7 to 10 business days
First itemUS$ 35.42US$ 35.42
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