Predicting Heart Failure (eBook)

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.

Preface vii

Abbreviations ix

Acknowledgment xvii

1 Invasive, Non-Invasive, Machine Learning, and Artificial Intelligence Based Methods for Prediction of Heart Failure 1
Hidayet Takci

2 Conventional Clinical Methods for Predicting Heart Disease 23
Aisha A-Mohannadi, Jayakanth Kunhoth, Al Anood Najeeb, Somaya Al-Maadeed, and Kishor Kumar Sadasivuni

3 Types of Biosensors and their Importance in Cardiovascular Applications 47
S Irem Kaya, Leyla Karadurmus, Ahmet Cetinkaya, Goksu Ozcelikay, and Sibel A Ozkan

4 Overview and Challenges of Wireless Communication and Power Transfer for Implanted Sensors 81
Mohamed Zied Chaari and Somaya Al-Maadeed

5 Minimally Invasive and Non-Invasive Sensor Technologies for Predicting Heart Failure: An Overview 109
Huseyin Enes Salman, Mahmoud Khatib A.A Al-Ruweidi, Hassen M Ouakad, and Huseyin C Yalcin

6 Artificial Intelligence Techniques in Cardiology: An Overview 139
Ikram-Ul Haq and Bo Xu

7 Utilizing Data Mining Classification Algorithms for Early Diagnosis of Heart Diseases 155
Ahmad Mousa Altamimi and Mohammad Azzeh

8 Applications of Machine Learning for Predicting Heart Failure 171
Sabri Boughorbel, Yassine Himeur, Huseyin Enes Salman, Faycal Bensaali,Faisal Farooq, and Huseyin C Yalcin

9 Machine Learning Techniques for Predicting and Managing Heart Failure 189
Dafni K Plati, Evanthia E Tripoliti, Georgia S Karanasiou, Aidonis Rammos,Aris Bechlioulis, Chris J Watson, Ken McDonald, Mark Ledwidge, Yorgos Goletsis, Katerina K Naka, and Dimitrios I Fotiadis

10 Clinical Applications of Artificial Intelligence in Early and Accurate Detection of Low- Concentration CVD Biomarkers 227
Meena Laad, Sajna M.S, Kishor Kumar Sadasivuni, and Sadiya Waseem

11 Commercial Non-Invasive and Invasive Devices for Heart Failure Prediction: A Review 243
Jayakanth Kunhoth, Nandhini Subramanian, and Ahmed Bouridane

12 Artificial Intelligence Based Commercial Non-Invasive and Invasive Devices for Heart Failure Diagnosis and Prediction 269
Kanchan Kulkarni, Eric M Isselbacher, and Antonis A Armoundas

13 Future Techniques and Perspectives on Implanted and Wearable Heart Failure Detection Devices 295
Muhammad E.H Chowdhury, Amith Khandaker, Yazan Qiblawey, Fahmida Haque, Maymouna Ezeddin, Tawsifur Rahman, Nabil Ibtehaz, and Khandaker Reajul Islam

Index 321