logo
Product categories

EbookNice.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link.  https://ebooknice.com/page/post?id=faq


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookNice Team

(Ebook) Predicting Heart Failure : Invasive, Non-Invasive, Machine Learning, and Artificial Intelligence Based Methods by Kishor Kumar Sadasivuni, Hassen M. Ouakad, Somaya Al-Maadeed, Huseyin C. Yalcin, Issam Bait Bahadur ISBN 9781119813019, 9781119813026, 9781119813033, 1119813018, 1119813026, 1119813034

  • SKU: EBN-45986486
Zoomable Image
$ 32 $ 40 (-20%)

Status:

Available

4.6

7 reviews
Instant download (eBook) Predicting Heart Failure : Invasive, Non-Invasive, Machine Learning, and Artificial Intelligence Based Methods after payment.
Authors:Kishor Kumar Sadasivuni, Hassen M. Ouakad, Somaya Al-Maadeed, Huseyin C. Yalcin, Issam Bait Bahadur
Pages:352 pages.
Year:2022
Editon:1
Publisher:John Wiley & Sons
Language:english
File Size:15.26 MB
Format:pdf
ISBNS:9781119813019, 9781119813026, 9781119813033, 1119813018, 1119813026, 1119813034
Categories: Ebooks

Product desciption

(Ebook) Predicting Heart Failure : Invasive, Non-Invasive, Machine Learning, and Artificial Intelligence Based Methods by Kishor Kumar Sadasivuni, Hassen M. Ouakad, Somaya Al-Maadeed, Huseyin C. Yalcin, Issam Bait Bahadur ISBN 9781119813019, 9781119813026, 9781119813033, 1119813018, 1119813026, 1119813034

PREDICTING HEART FAILURE 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: Discussion of the main characteristics of cardiovascular biosensors, along with their open issues for development and application Summary of the difficulties of wireless sensor communication and power transfer, and the utility of artificial intelligence in cardiology Coverage of data mining classification techniques, applied machine learning and advanced methods for estimating HF severity and diagnosing and predicting heart failure Discussion of the risks and issues associated with the remote monitoring system Assessment of the potential applications and future of implantable and wearable devices in heart failure prediction and detection Artificial intelligence in mobile monitoring technologies to provide clinicians with improved treatment options, ultimately easing access to healthcare by all patient populations. 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.
*Free conversion of into popular formats such as PDF, DOCX, DOC, AZW, EPUB, and MOBI after payment.

Related Products