Search Results - Watson's lemma~

Emma Watson the Watson completed by Aiken, Joan

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The semiotics of heritage tourism by Waterton, Emma

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The cultural moment in tourism by Smith, Laurajane

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500 jus dan smoothie by Watson, Christine

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The complete surfaces and finishes directory paint, plaster, wallpaper, tile, wood, metal, glass by Scattergood, Emma

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DISCOVERY THROUGH ACTIVITY IDEAS AND RESOURCES FOR APPLYING RECOVERY THROUGH ACTIVITY IN PRACTICE

Table of Contents: “…Adopting recovery through activity across adult community and inpatient mental health services / Amy Mitchell -- Embedding recovery through activity service-wide / Amy Mitchell and Sarah Morecroft -- Applying recovery through activity in community and inpatient services for older adults / Gemma Perrin and Hannah Hazelwood -- Continuing recovery through activity opportunities for older adults in a peer support group / Joan Holland and Alison Butters -- Applying recovery through activity in an inpatient child and adolescent mental health service (CAMHS) / Carly Watson, Isla Garrick and Hazel Watkiss -- Applying recovery through activity in a prison service / Xenia Denson and Charlotte Wise -- Applying recovery through activity in a secure learning disability service / Deborah Haworth -- Applying recovery through activity in a neuropsychiatry service / Kimberley Connell, Nataliya Williams and Jess Powell -- Adapting recovery through activity for one-to-one sessions / Rachael Kirtley and Ashley Lister -- Adapting recovery through activity for virtual groups and one-to-one sessions / Gemma Dorer and Sarah Long -- Adapting recovery through activity for a virtual group using PowerPoint / Niamh Gibney, Una Belton, Hugh Bulfin, Laura Hackett, Bláithín Swinburne and Lucinda Fallon -- Extending the content of recovery through activity sections: Leisure activities, Creative activities, Technological activities, Physical activities , Outdoor activities, Faith activities, Self-care activities, Domestic activities, Caring activities, Vocational activities, Social activities, Community activities.…”
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Sherlock Holmes Pilu Seorang Bangsawan, Misteri Mahkota Permata Beril by Doyle, Arthur Conan

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Kumar & Clark's clinical medicine

Table of Contents: “…Harries, F. Vaz, and S. Verma -- Neurological disease / C.R.A. Clarke -- Psychological medicine / P.D. …”
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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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