Machine learning for healthcare applications / (Record no. 69517)

000 -LEADER
fixed length control field 04375cam a22005898i 4500
001 - CONTROL NUMBER
control field on1243906209
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220711203654.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 210324s2021 nju ob 001 0 eng
019 ## -
-- 1248737898
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781119792598
-- (epub)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1119792592
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781119792604
-- (adobe pdf)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1119792606
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
-- (cloth)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781119792611
-- (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1119792614
-- (electronic bk.)
029 1# - (OCLC)
OCLC library identifier AU@
System control number 000068919438
082 00 - CLASSIFICATION NUMBER
Call Number 610.285
245 00 - TITLE STATEMENT
Title Machine learning for healthcare applications /
300 ## - PHYSICAL DESCRIPTION
Number of Pages 1 online resource
520 ## - SUMMARY, ETC.
Summary, etc "When considering the idea of using machine learning in healthcare, it is a Herculean task to present the entire gamut of information in the field of intelligent systems. It is, therefore the objective of this book to keep the presentation narrow and intensive. This approach is distinct from others in that it presents detailed computer simulations for all models presented with explanations of the program code. It includes unique and distinctive chapters on disease diagnosis, telemedicine, medical imaging, smart health monitoring, social media healthcare, and machine learning for COVID-19. These chapters help develop a clear understanding of the working of an algorithm while strengthening logical thinking. In this environment, answering a single question may require accessing several data sources and calling on sophisticated analysis tools. While data integration is a dynamic research area in the database community, the specific needs of research have led to the development of numerous middleware systems that provide seamless data access in a result-driven environment. Since this book is intended to be useful to a wide audience, students, researchers and scientists from both academia and industry may all benefit from this material. It contains a comprehensive description of issues for healthcare data management and an overview of existing systems, making it appropriate for introductory and instructional purposes. Prerequisites are minimal; the readers are expected to have basic knowledge of machine learning. This book is divided into 22 real-time innovative chapters which provide a variety of application examples in different domains. These chapters illustrate why traditional approaches often fail to meet customers' needs. The presented approaches provide a comprehensive overview of current technology. Each of these chapters, which are written by the main inventors of the presented systems, specifies requirements and provides a description of both the chosen approach and its implementation. Because of the self-contained nature of these chapters, they may be read in any order. Each of the chapters use various technical terms which involve expertise in machine learning and computer science"--
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
General subdivision Data processing.
650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1
General subdivision Data processing.
700 1# - AUTHOR 2
Author 2 Mohanty, Sachi Nandan,
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1002/9781119792611
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Hoboken, NJ :
-- Wiley-Scrivener,
-- 2021.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
520 ## - SUMMARY, ETC.
-- Provided by publisher.
588 ## -
-- Description based on print version record and CIP data provided by publisher; resource not viewed.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Medical informatics.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Machine learning.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Medicine
650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Machine learning.
-- (OCoLC)fst01004795
650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Medical informatics.
-- (OCoLC)fst01014175
650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Medicine
-- (OCoLC)fst01014924
994 ## -
-- 92
-- DG1

No items available.