Advances of Machine Learning for Knowledge Mining in Electronic Health Records

Language: English

Published by Taylor and Francis Ltd, GB, 2025

1032526106 / 9781032526102

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  • New
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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 recordsCovers information extraction, standards for meta-data, reuse of metadata for clinical research, and organized and unstructured dataDiscusses supervised and unsupervised learning in electronic health recordsDescribes clustering and classification techniques for organized, semi- structured, and unstructured data from electronic health recordsThis 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 # LU-9781032526102

Title
Advances of Machine Learning for Knowledge Mining in Electronic Health Records
Author
P. Mohamed Fathimal
Publisher
Taylor and Francis Ltd, GB
Publication year
2025
Condition
New
Binding
Hardback
Language
English
ISBN 10
1032526106
ISBN 13
9781032526102
Item weight
690 grams

Rarewaves.com UK

London, United Kingdom

5-star seller

AbeBooks seller since June 11, 2025

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