{"product_id":"predicting-heart-failure-isbn-9781119813019","title":"Predicting Heart Failure","description":"\u003cb\u003ePREDICTING HEART FAILURE\u003c\/b\u003e \u003cp\u003e\u003ci\u003ePredicting Heart Failure: Invasive, Non-Invasive, Machine Learning and Artificial Intelligence Based Methods\u003c\/i\u003e focuses on the mechanics and symptoms of heart failure and various approaches, including conventional and modern techniques to diagnose it.  \u003c\/p\u003e\u003cp\u003eThis book also provides a comprehensive but concise guide to all modern cardiological practice, emphasizing practical clinical management in many different contexts. \u003ci\u003ePredicting Heart Failure\u003c\/i\u003e 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:  \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eDiscussion of the main characteristics of cardiovascular biosensors, along with their open issues for development and application\u003c\/li\u003e \u003cli\u003eSummary of the difficulties of wireless sensor communication and power transfer, and the utility of artificial intelligence in cardiology\u003c\/li\u003e \u003cli\u003eCoverage of data mining classification techniques, applied machine learning and advanced methods for estimating HF severity and diagnosing and predicting heart failure\u003c\/li\u003e \u003cli\u003eDiscussion of the risks and issues associated with the remote monitoring system\u003c\/li\u003e \u003cli\u003eAssessment of the potential applications and future of implantable and wearable devices in heart failure prediction and detection \u003c\/li\u003e \u003cli\u003eArtificial intelligence in mobile monitoring technologies to provide clinicians with improved treatment options, ultimately easing access to healthcare by all patient populations.\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003e Providing the latest research data for the diagnosis and treatment of heart failure, \u003ci\u003ePredicting Heart Failure: Invasive, Non-Invasive, Machine Learning and Artificial Intelligence Based Methods\u003c\/i\u003e is an excellent resource for nurses, nurse practitioners, physician assistants, medical students, and general practitioners to gain a better understanding of bedside cardiology. \u003c\/p\u003e\u003cp\u003ePreface vii\u003c\/p\u003e \u003cp\u003eAbbreviations ix\u003c\/p\u003e \u003cp\u003eAcknowledgment xvii\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Invasive, Non-Invasive, Machine Learning, and Artificial Intelligence Based Methods for Prediction of Heart Failure \u003c\/b\u003e\u003cb\u003e1\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eHidayet Takcı\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Conventional Clinical Methods for Predicting Heart Disease \u003c\/b\u003e\u003cb\u003e23\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eAisha A-Mohannadi, Jayakanth Kunhoth, Al Anood Najeeb, Somaya Al-Maadeed, and Kishor Kumar Sadasivuni\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Types of Biosensors and their Importance in Cardiovascular Applications \u003c\/b\u003e\u003cb\u003e47\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eS Irem Kaya, Leyla Karadurmuş, Ahmet Cetinkaya, Goksu Ozcelikay, and Sibel A Ozkan\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Overview and Challenges of Wireless Communication and Power Transfer for Implanted Sensors \u003c\/b\u003e\u003cb\u003e81\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eMohamed Zied Chaari and Somaya Al-Maadeed\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Minimally Invasive and Non-Invasive Sensor Technologies for Predicting Heart Failure: An Overview \u003c\/b\u003e\u003cb\u003e109\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eHuseyin Enes Salman, Mahmoud Khatib A.A Al-Ruweidi, Hassen M Ouakad, and Huseyin C Yalcin\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Artificial Intelligence Techniques in Cardiology: An Overview \u003c\/b\u003e\u003cb\u003e139\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eIkram-Ul Haq and Bo Xu\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Utilizing Data Mining Classification Algorithms for Early Diagnosis of Heart Diseases \u003c\/b\u003e\u003cb\u003e155\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eAhmad Mousa Altamimi and Mohammad Azzeh\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Applications of Machine Learning for Predicting Heart Failure \u003c\/b\u003e\u003cb\u003e171\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eSabri Boughorbel, Yassine Himeur, Huseyin Enes Salman, Faycal Bensaali,Faisal Farooq, and Huseyin C Yalcin\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Machine Learning Techniques for Predicting and Managing Heart Failure \u003c\/b\u003e\u003cb\u003e189\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eDafni K Plati, Evanthia E Tripoliti, Georgia S Karanasiou, Aidonis Rammos,\u003c\/i\u003e\u003ci\u003eAris Bechlioulis, Chris J Watson, Ken McDonald, Mark Ledwidge, Yorgos Goletsis, Katerina K Naka, and Dimitrios I Fotiadis\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Clinical Applications of Artificial Intelligence in Early and Accurate Detection of Low- Concentration CVD Biomarkers \u003c\/b\u003e\u003cb\u003e227\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eMeena Laad, Sajna M.S, Kishor Kumar Sadasivuni, and Sadiya Waseem\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Commercial Non-Invasive and Invasive Devices for Heart Failure Prediction: A Review \u003ci\u003e243\u003cbr\u003e\u003c\/i\u003e\u003c\/b\u003e\u003ci\u003eJayakanth Kunhoth, Nandhini Subramanian, and Ahmed Bouridane\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Artificial Intelligence Based Commercial Non-Invasive and Invasive Devices for Heart Failure Diagnosis and Prediction \u003c\/b\u003e\u003cb\u003e269\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eKanchan Kulkarni, Eric M Isselbacher, and Antonis A Armoundas\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Future Techniques and Perspectives on Implanted and Wearable Heart \u003c\/b\u003e\u003cb\u003eFailure Detection Devices \u003c\/b\u003e\u003cb\u003e295\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eMuhammad E.H Chowdhury, Amith Khandaker, Yazan Qiblawey, Fahmida Haque, \u003c\/i\u003e\u003ci\u003eMaymouna Ezeddin, Tawsifur Rahman, Nabil Ibtehaz, and Khandaker Reajul Islam\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIndex 321\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAbout the Editors\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eDr Kishor Kumar Sadasivuni,\u003c\/b\u003e Center for Advanced Materials, Qatar University, Qatar  \u003c\/p\u003e\u003cp\u003e\u003cb\u003eDr Hassen M. Ouakad,\u003c\/b\u003e Department of Mechanical and Industrial Engineering, Sultan Qaboos University, Oman  \u003c\/p\u003e\u003cp\u003e\u003cb\u003eProf. Somaya Al-Maadeed,\u003c\/b\u003e Department of Computer Science and Engineering, Qatar University, Qatar  \u003c\/p\u003e\u003cp\u003e\u003cb\u003eDr Huseyin C. Yalcin, Biomedical Research Center, Qatar University, Qatar  \u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eDr Issam Bait Bahadur,\u003c\/b\u003e Department of Mechanical and Industrial Engineering, Sultan Qaboos University, Oman  \u003c\/p\u003e\u003cp\u003eThis 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.   \u003c\/p\u003e\u003cp\u003e\u003ci\u003ePredicting Heart Failure: Invasive, Non-Invasive, Machine Learning and Artificial Intelligence Based Methods\u003c\/i\u003e focuses on the mechanics and symptoms of heart failure and various approaches, including conventional and modern techniques to diagnose it. \u003c\/p\u003e \u003cp\u003eThis book also provides a comprehensive but concise guide to all modern cardiological practice, emphasizing practical clinical management in many different contexts. \u003ci\u003ePredicting Heart Failure\u003c\/i\u003e 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:  \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eDiscussion of the main characteristics of cardiovascular biosensors, along with their open issues for development and application\u003c\/li\u003e \u003cli\u003eSummary of the difficulties of wireless sensor communication and power transfer, and the utility of artificial intelligence in cardiology\u003c\/li\u003e \u003cli\u003eCoverage of data mining classification techniques, applied machine learning and advanced methods for estimating HF severity and diagnosing and predicting heart failure\u003c\/li\u003e \u003cli\u003eDiscussion of the risks and issues associated with the remote monitoring system\u003c\/li\u003e \u003cli\u003eAssessment of the potential applications and future of implantable and wearable devices in heart failure prediction and detection \u003c\/li\u003e \u003cli\u003eArtificial intelligence in mobile monitoring technologies to provide clinicians with improved treatment options, ultimately easing access to healthcare by all patient populations.\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003e Providing the latest research data for the diagnosis and treatment of heart failure, \u003ci\u003ePredicting Heart Failure: Invasive, Non-Invasive, Machine Learning and Artificial Intelligence Based Methods\u003c\/i\u003e is an excellent resource for nurses, nurse practitioners, physician assistants, medical students, and general practitioners to gain a better understanding of bedside cardiology.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989840314597,"sku":"NP9781119813019","price":188.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119813019.jpg?v=1761785642","url":"https:\/\/k12savings.com\/es\/products\/predicting-heart-failure-isbn-9781119813019","provider":"K12savings","version":"1.0","type":"link"}