Search Results - "Artificial Intelligence"

Modeling legal argument reasoning with cases and hypotheticals by Ashley, Kevin D

Subjects: “…Artificial intelligence…”
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Overlord Protocol by WALDEN, MARK

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Techniques and Environments for Big Data Analysis Parallel, Cloud, and Grid Computing

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Knowledge oriented software design extended papers from the IFIP TC 12 Workshop on Artificial Intelligence from the Information Processing Perspective, AIFIPP '92, Madrid, Spain, 14-15 September, 1992

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Predicting Heart Failure Invasive, Non-Invasive, Machine Learning No Artificial Intelligence Based Methods

Table of Contents: “…Preface vii Abbreviations ix Acknowledgment xvii 1 Invasive, Non-Invasive, Machine Learning, and Artificial Intelligence Based Methods for Prediction of Heart Failure 1Hidayet Takci 2 Conventional Clinical Methods for Predicting Heart Disease 23Aisha A-Mohannadi, Jayakanth Kunhoth, Al Anood Najeeb, Somaya Al-Maadeed, and Kishor Kumar Sadasivuni 3 Types of Biosensors and their Importance in Cardiovascular Applications 47S 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 81Mohamed Zied Chaari and Somaya Al-Maadeed 5 Minimally Invasive and Non-Invasive Sensor Technologies for Predicting Heart Failure: An Overview 109Huseyin Enes Salman, Mahmoud Khatib A.A Al-Ruweidi, Hassen M Ouakad, and Huseyin C Yalcin 6 Artificial Intelligence Techniques in Cardiology: An Overview 139Ikram-Ul Haq and Bo Xu 7 Utilizing Data Mining Classification Algorithms for Early Diagnosis of Heart Diseases 155Ahmad Mousa Altamimi and Mohammad Azzeh 8 Applications of Machine Learning for Predicting Heart Failure 171Sabri Boughorbel, Yassine Himeur, Huseyin Enes Salman, Faycal Bensaali,Faisal Farooq, and Huseyin C Yalcin 9 Machine Learning Techniques for Predicting and Managing Heart Failure 189Dafni 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 227Meena Laad, Sajna M.S, Kishor Kumar Sadasivuni, and Sadiya Waseem 11 Commercial Non-Invasive and Invasive Devices for Heart Failure Prediction: A Review 243Jayakanth Kunhoth, Nandhini Subramanian, and Ahmed Bouridane 12 Artificial Intelligence Based Commercial Non-Invasive and Invasive Devices for Heart Failure Diagnosis and Prediction 269Kanchan Kulkarni, Eric M Isselbacher, and Antonis A Armoundas 13 Future Techniques and Perspectives on Implanted and Wearable Heart Failure Detection Devices 295Muhammad E.H Chowdhury, Amith Khandaker, Yazan Qiblawey, Fahmida Haque, Maymouna Ezeddin, Tawsifur Rahman, Nabil Ibtehaz, and Khandaker Reajul Islam Index 321…”
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PREDICTING HEART FAILURE INVASIVE, NON-INVASIVE, MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE BASED METHODS

Table of Contents: “…Preface vii Abbreviations ix Acknowledgment xvii 1 Invasive, Non-Invasive, Machine Learning, and Artificial Intelligence Based Methods for Prediction of Heart Failure 1Hidayet Takci 2 Conventional Clinical Methods for Predicting Heart Disease 23Aisha A-Mohannadi, Jayakanth Kunhoth, Al Anood Najeeb, Somaya Al-Maadeed, and Kishor Kumar Sadasivuni 3 Types of Biosensors and their Importance in Cardiovascular Applications 47S 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 81Mohamed Zied Chaari and Somaya Al-Maadeed 5 Minimally Invasive and Non-Invasive Sensor Technologies for Predicting Heart Failure: An Overview 109Huseyin Enes Salman, Mahmoud Khatib A.A Al-Ruweidi, Hassen M Ouakad, and Huseyin C Yalcin 6 Artificial Intelligence Techniques in Cardiology: An Overview 139Ikram-Ul Haq and Bo Xu 7 Utilizing Data Mining Classification Algorithms for Early Diagnosis of Heart Diseases 155Ahmad Mousa Altamimi and Mohammad Azzeh 8 Applications of Machine Learning for Predicting Heart Failure 171Sabri Boughorbel, Yassine Himeur, Huseyin Enes Salman, Faycal Bensaali,Faisal Farooq, and Huseyin C Yalcin 9 Machine Learning Techniques for Predicting and Managing Heart Failure 189Dafni 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 227Meena Laad, Sajna M.S, Kishor Kumar Sadasivuni, and Sadiya Waseem 11 Commercial Non-Invasive and Invasive Devices for Heart Failure Prediction: A Review 243Jayakanth Kunhoth, Nandhini Subramanian, and Ahmed Bouridane 12 Artificial Intelligence Based Commercial Non-Invasive and Invasive Devices for Heart Failure Diagnosis and Prediction 269Kanchan Kulkarni, Eric M Isselbacher, and Antonis A Armoundas 13 Future Techniques and Perspectives on Implanted and Wearable Heart Failure Detection Devices 295Muhammad E.H Chowdhury, Amith Khandaker, Yazan Qiblawey, Fahmida Haque, Maymouna Ezeddin, Tawsifur Rahman, Nabil Ibtehaz, and Khandaker Reajul Islam Index 321…”
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Knowledge engineering knowledge acquisition, knowledge representation, the role of the knowledge engineer, and domains fertile to AI implementation by Chorafas, Dimitris N

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Intelligent learning environments and knowledge acquisition in physics

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Advanced engineering informatics

Subjects: “…Artificial intelligence Periodicals Data processing…”
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Knowledge-based intelligent information engineering systems and allied technologies KES 2002

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Cooperative control of distributed multi-agent systems

Subjects: “…Distributed artificial intelligence…”
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Distributed intelligence in design

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THE COMPUTER AFTER ME Awareness and Self-Awareness in Autonomic Systems

Subjects: “…Artificial intelligence…”
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Intelligent computer aided design proceedings of the IFIP WG 5.2 Working Conference on Intelligent Computer Aided Design (IntCAD91), Columbus, OH, USA, 30 September 1991-3 October...

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HBR Guide to AI Basics for Managers

Subjects: “…Artificial intelligence…”
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Bioinformatics the machine learning approach by Baldi, Pierre

Subjects: “…Artificial intelligence…”
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Intelligent problem solving methodologies and approaches proceedings of the ..held June 19 - 22, 2000

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Metalevel architectures and separation of crosscutting concerns proceedings of the ...held September 25 - 28, 2001

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Experience management foundations, development methodology, and Internet-based applications by Bergmann, R. Ralph

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New Trends in Software Methodologies, Tools and Techniques Proceedings of the Eighth SoMeT 09 by Marik, V. Vladimir

Subjects: “…Artificial intelligence Congresses…”
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