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Predicting Heart Failure: Invasive, Non-Invasive, Machine Learning and Artificial Intelligence Based Methods focuses on the mechanics and symptoms of heart failure and various approaches, including conventional and modern techniques to diagnose it.
This book also provides a comprehensive but concise guide to all modern cardiological practice, emphasizing practical clinical management in many different contexts. Predicting Heart Failure supplies readers with trustworthy insights into all aspects of heart failure, including essential background information on clinical practice guidelines, in-depth, peer-reviewed articles, and broad coverage of this fast-moving field. Readers will also find:
Providing the latest research data for the diagnosis and treatment of heart failure, Predicting Heart Failure: Invasive, Non-Invasive, Machine Learning and Artificial Intelligence Based Methods is an excellent resource for nurses, nurse practitioners, physician assistants, medical students, and general practitioners to gain a better understanding of bedside cardiology.
Author: Kishor Kumar Sadasivuni
ISBN-10: 1119813018
ISBN-13: 9781119813019
Publisher: Wiley
Language: English
Published: 04/04/2022
Pages: 352
Format: Hardcover
Weight: 1.75lbs
Size: 9.69h x 6.61w x 0.87d
About the Editors
Dr Kishor Kumar Sadasivuni, Center for Advanced Materials, Qatar University, Qatar
Dr Hassen M. Ouakad, Department of Mechanical and Industrial Engineering, Sultan Qaboos University, Oman
Prof. Somaya Al-Maadeed, Department of Computer Science and Engineering, Qatar University, Qatar
Dr Huseyin C. Yalcin, Biomedical Research Center, Qatar University, Qatar
Dr Issam Bait Bahadur, Department of Mechanical and Industrial Engineering, Sultan Qaboos University, Oman
This publication was supported by Qatar University Internal Grant No. IRCC-2020-013 and Sultan Qaboos University through Grant # CL/SQU-QU/ENG/20/01, respectively. The findings achieved herein are solely the responsibility of the authors.
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