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Authored by Kishor Kumar Sadasivuni, Hassen M. Ouakad, Somaya Al-Maadeed, Huseyin C. Yalcin, and Issam Bait Bahadur, “Predicting Heart Failure: Invasive, Non-Invasive, Machine Learning and Artificial Intelligence Based Methods” is a valuable resource for medical professionals seeking to enhance their understanding of heart failure diagnosis and treatment.
This book delves into the intricacies of heart failure, covering its mechanics and symptoms, as well as conventional and modern techniques for diagnosis. From cardiovascular biosensors to wireless sensor communication and power transfer, the authors provide a comprehensive overview of the latest developments in the field.
“Predicting Heart Failure” is an essential guide for nurses, nurse practitioners, physician assistants, medical students, and general practitioners looking to stay abreast of the latest research and advancements in heart failure prediction and detection. The book emphasizes practical clinical management, providing trustworthy insights into all aspects of heart failure, including:
With the field of cardiology rapidly evolving, it’s essential for medical professionals to stay up-to-date on the latest research and advancements. “Predicting Heart Failure” provides readers with the latest research data for the diagnosis and treatment of heart failure, empowering them to provide better patient care and improve health outcomes.
Publication details: Publisher – Wiley; 1st edition (April 5, 2022); Language – English; ISBN – 1119813018
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