K Kumar Sadasivun
Predicting Heart Failure: Invasive, Non-Invasive, Machine Learning and Artificial Intelligence Based Methods
Predicting Heart Failure: Invasive, Non-Invasive, Machine Learning and Artificial Intelligence Based Methods
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Excellent- More about Predicting Heart Failure: Invasive, Non-Invasive, Machine Learning and Artificial Intelligence Based Methods
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 to diagnosing it. It also provides a comprehensive guide to modern cardiological practice, emphasizing practical clinical management in many different contexts. The book discusses cardiovascular biosensors, wireless sensor communication, power transfer, artificial intelligence, data mining classification techniques, applied machine learning, advanced methods for estimating HF severity, diagnosing, and predicting heart failure, remote monitoring systems, and the potential applications and future of implantable and wearable devices in heart failure prediction and detection. It is an excellent resource for nurses, nurse practitioners, physician assistants, medical students, and general practitioners to gain a better understanding of bedside cardiology.
Format: Hardback
Length: 352 pages
Publication date: 28 April 2022
Publisher: John Wiley and Sons Ltd
Predicting Heart Failure: Invasive, Non-Invasive, Machine Learning, and Artificial Intelligence-Based Methods delves into the intricate mechanics and symptoms of heart failure, exploring a range of approaches, from conventional to modern techniques, for its diagnosis. This comprehensive yet concise book serves as a valuable guide to modern cardiological practice, emphasizing practical clinical management across various contexts.
In addition to providing a wealth of information, this book offers readers insightful perspectives on all aspects of heart failure, encompassing essential background knowledge on clinical practice guidelines, in-depth, peer-reviewed articles, and extensive coverage of this rapidly evolving field. Readers will find:
A discussion of the primary characteristics of cardiovascular biosensors, along with their ongoing challenges and potential applications
A summary of the complexities involved in wireless sensor communication and power transfer, highlighting the role of artificial intelligence in cardiology
An exploration of data mining classification techniques, applied machine learning, and advanced methods for estimating heart failure severity and diagnosing and predicting heart failure
A consideration of the risks and considerations associated with remote monitoring systems, as well as their potential applications and future impact
An assessment of the potential applications and future of implantable and wearable devices in heart failure prediction and detection
Artificial intelligence in mobile monitoring technologies, empowering clinicians with improved treatment options and ultimately enhancing access to healthcare for all patient populations.
By presenting the latest research data in the diagnosis and treatment of heart failure, Predicting Heart Failure: Invasive, Non-Invasive, Machine Learning, and Artificial Intelligence-Based Methods serves as an invaluable resource for nurses, healthcare professionals, and researchers alike.
Weight: 838g
Dimension: 176 x 250 x 27 (mm)
ISBN-13: 9781119813019
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