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AI-enabled multiple-criteria decision-making approaches for healthcare management

Record Type:	Electronic resources : Monograph/item
Title/Author:	AI-enabled multiple-criteria decision-making approaches for healthcare management/ Sandeep Kautish, and Gaurav Dhiman, editors.
remainder title:	Artificial intelligence-enabled multiple-criteria decision-making approaches for healthcare management
other author:	Kautish, Sandeep,
Published:	Hershey, Pennsylvania :IGI Global, : 2022.,
Description:	1 online resource (274 p.) j:ill. (chiefly col.)
[NT 15003449]:	Chapter 1. Real-time detection of cardiac arrest using deep learning -- Chapter 2. A study and analysis of deep neural networks for cancer using histopathology images -- Chapter 3. Artificial intelligence based on IoT for healthcare-- Chapter 4. Secure medical data transmission over wireless body area network using blockchain -- Chapter 5. AI-enabled augmented reality-based shared collaborative experience -- Chapter 6. A comparative study with linear regression and linear regression with fuzzy data for the same data set: LRFD -- Chapter 7. A comparative study of fuzzy linear and multi-objective optimization -- Chapter 8. Clustering and regression analysis on COVID-19 in India using python -- Chapter 9.Acomprehensive study of various fuzzy c-means clustering algorithms -- Chapter 10. Survey or review on the deep learning techniques for retinal image segmentation in predicting/diagnosing diabetic retinopathy -- Chapter 11. Adaptive clinical treatments and reinforcement learning for automatic disease diagnosis -- Chapter 12. AI-enabled internet of nano things methodology for healthcare information management.
Subject:	Medical care - Decision making -
Online resource:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-6684-4405-4
ISBN:	9781668444078

AI-enabled multiple-criteria decision-making approaches for healthcare management
AI-enabled multiple-criteria decision-making approaches for healthcare management[electronic resource] /Artificial intelligence-enabled multiple-criteria decision-making approaches for healthcare managementSandeep Kautish, and Gaurav Dhiman, editors. - Hershey, Pennsylvania :IGI Global,2022. - 1 online resource (274 p.) j:ill. (chiefly col.)

Includes bibliographical references and index.

Chapter 1. Real-time detection of cardiac arrest using deep learning -- Chapter 2. A study and analysis of deep neural networks for cancer using histopathology images -- Chapter 3. Artificial intelligence based on IoT for healthcare-- Chapter 4. Secure medical data transmission over wireless body area network using blockchain -- Chapter 5. AI-enabled augmented reality-based shared collaborative experience -- Chapter 6. A comparative study with linear regression and linear regression with fuzzy data for the same data set: LRFD -- Chapter 7. A comparative study of fuzzy linear and multi-objective optimization -- Chapter 8. Clustering and regression analysis on COVID-19 in India using python -- Chapter 9.Acomprehensive study of various fuzzy c-means clustering algorithms -- Chapter 10. Survey or review on the deep learning techniques for retinal image segmentation in predicting/diagnosing diabetic retinopathy -- Chapter 11. Adaptive clinical treatments and reinforcement learning for automatic disease diagnosis -- Chapter 12. AI-enabled internet of nano things methodology for healthcare information management.

"The success of healthcare decision-making lies in whether healthcare staff, patients, and healthcare organization managers can comprehensively understand the choices and consider future implications to make the best decision possible, so this book investigates practical multiple criteria decision analysis applications and cases for healthcare management"--

ISBN: 9781668444078Subjects--Topical Terms:

3730041
Medical care
--Decision makingIndex Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: R859.7.D42 / A44 2022eb

Dewey Class. No.: 610.285 $223

National Library of Medicine Call No.: W 26.55.D2 / A44 2022eb

AI-enabled multiple-criteria decision-making approaches for healthcare management
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260 $a Hershey, Pennsylvania : $b IGI Global, $c 2022.
300 $a 1 online resource (274 p.) j: $b ill. (chiefly col.)
504 $a Includes bibliographical references and index.
505 0 $a Chapter 1. Real-time detection of cardiac arrest using deep learning -- Chapter 2. A study and analysis of deep neural networks for cancer using histopathology images -- Chapter 3. Artificial intelligence based on IoT for healthcare-- Chapter 4. Secure medical data transmission over wireless body area network using blockchain -- Chapter 5. AI-enabled augmented reality-based shared collaborative experience -- Chapter 6. A comparative study with linear regression and linear regression with fuzzy data for the same data set: LRFD -- Chapter 7. A comparative study of fuzzy linear and multi-objective optimization -- Chapter 8. Clustering and regression analysis on COVID-19 in India using python -- Chapter 9.Acomprehensive study of various fuzzy c-means clustering algorithms -- Chapter 10. Survey or review on the deep learning techniques for retinal image segmentation in predicting/diagnosing diabetic retinopathy -- Chapter 11. Adaptive clinical treatments and reinforcement learning for automatic disease diagnosis -- Chapter 12. AI-enabled internet of nano things methodology for healthcare information management.
520 $a "The success of healthcare decision-making lies in whether healthcare staff, patients, and healthcare organization managers can comprehensively understand the choices and consider future implications to make the best decision possible, so this book investigates practical multiple criteria decision analysis applications and cases for healthcare management"-- $c Provided by publisher.
650 0 $a Medical care $x Decision making $x Data processing. $3 3730041
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650 2 2 $a Medical Informatics $v Congresses. $3 1003414
655 4 $a Electronic books. $2 lcsh $3 542853
700 1 $a Kautish, Sandeep, $d 1981- $3 3730039
700 1 $a Dhiman, Gaurav, $d 1993- $3 3730040
710 2 $a IGI Global. $3 1361470
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