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ویرایش: [1 ed.] نویسندگان: R. J. Hemalatha (editor), D. Akila (editor), D. Balaganesh (editor), Anand Paul (editor) سری: ISBN (شابک) : 1119768837, 9781119768838 ناشر: Wiley-Scrivener سال نشر: 2022 تعداد صفحات: 336 زبان: English فرمت فایل : EPUB (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود) حجم فایل: 5 Mb
در صورت تبدیل فایل کتاب The Internet of Medical Things (IoMT): Healthcare Transformation (Advances in Learning Analytics for Intelligent Cloud-IoT Systems) به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
توجه داشته باشید کتاب اینترنت اشیاء پزشکی (IoMT): تحول مراقبت های بهداشتی (پیشرفت در تجزیه و تحلیل یادگیری برای سیستم های هوشمند Cloud-IoT) نسخه زبان اصلی می باشد و کتاب ترجمه شده به فارسی نمی باشد. وبسایت اینترنشنال لایبرری ارائه دهنده کتاب های زبان اصلی می باشد و هیچ گونه کتاب ترجمه شده یا نوشته شده به فارسی را ارائه نمی دهد.
این نشریه بهموقع با ارائه یک افزونه ضروری به مواد مرجع موجود در زمینه IoMT، طیف وسیعی از تحقیقات کاربردی در مورد مراقبتهای بهداشتی، دادهکاوی زیستپزشکی را پوشش میدهد. و امنیت و حریم خصوصی سوابق بهداشتی.
ابزارهای IoMT با توانایی خود در جمع آوری، تجزیه و تحلیل و انتقال داده های بهداشتی به سرعت در حال تغییر در ارائه مراقبت های بهداشتی هستند. برای بیماران و پزشکان، این برنامهها نقش اصلی را در ردیابی و پیشگیری از بیماریهای مزمن ایفا میکنند - و آماده تکامل آینده مراقبتها هستند.
در این کتاب، نویسندگان کاربردهای بالقوه موجی از ابزارهای مبتنی بر حسگر - از جمله ابزارهای پوشیدنی و دستگاههای مستقل برای نظارت از راه دور بیمار - و ازدواج اینترنت را بررسی میکنند. -دستگاه های پزشکی متصل با اطلاعات بیمار که در نهایت اکوسیستم IoMT را متمایز می کند.
این کتاب نشان میدهد که ارتباط بین دستگاههای پزشکی و حسگرها مدیریت گردش کار بالینی را سادهتر میکند و منجر به بهبود کلی در مراقبت از بیمار، هم در داخل مراکز مراقبت و هم در مکانهای دوردست میشود. span>
Providing an essential addition to the reference material available in the field of IoMT, this timely publication covers a range of applied research on healthcare, biomedical data mining, and the security and privacy of health records.
With their ability to collect, analyze and transmit health data, IoMT tools are rapidly changing healthcare delivery. For patients and clinicians, these applications are playing a central part in tracking and preventing chronic illnesses ― and they are poised to evolve the future of care.
In this book, the authors explore the potential applications of a wave of sensor-based tools―including wearables and stand-alone devices for remote patient monitoring―and the marriage of internet-connected medical devices with patient information that ultimately sets the IoMT ecosystem apart.
This book demonstrates the connectivity between medical devices and sensors is streamlining clinical workflow management and leading to an overall improvement in patient care, both inside care facilities and in remote locations.
Cover Half-Title Page Series Page Title Page Copyright Page Contents Preface 1 In Silico Molecular Modeling and Docking Analysis in Lung Cancer Cell Proteins 1.1 Introduction 1.2 Methodology 1.2.1 Sequence of Protein 1.2.2 Homology Modeling 1.2.3 Physiochemical Characterization 1.2.4 Determination of Secondary Models 1.2.5 Determination of Stability of Protein Structures 1.2.6 Identification of Active Site 1.2.7 Preparation of Ligand Model 1.2.8 Docking of Target Protein and Phytocompound 1.3 Results and Discussion 1.3.1 Determination of Physiochemical Characters 1.3.2 Prediction of Secondary Structures 1.3.3 Verification of Stability of Protein Structures 1.3.4 Identification of Active Sites 1.3.5 Target Protein-Ligand Docking 1.4 Conclusion References 2 Medical Data Classification in Cloud Computing Using Soft Computing With Voting Classifier: A Review 2.1 Introduction 2.1.1 Security in Medical Big Data Analytics 2.1.1.1 Capture 2.1.1.2 Cleaning 2.1.1.3 Storage 2.1.1.4 Security 2.1.1.5 Stewardship 2.2 Access Control–Based Security 2.2.1 Authentication 2.2.1.1 User Password Authentication 2.2.1.2 Windows-Based User Authentication 2.2.1.3 Directory-Based Authentication 2.2.1.4 Certificate-Based Authentication 2.2.1.5 Smart Card–Based Authentication 2.2.1.6 Biometrics 2.2.1.7 Grid-Based Authentication 2.2.1.8 Knowledge-Based Authentication 2.2.1.9 Machine Authentication 2.2.1.10 One-Time Password (OTP) 2.2.1.11 Authority 2.2.1.12 Global Authorization 2.3 System Model 2.3.1 Role and Purpose of Design 2.3.1.1 Patients 2.3.1.2 Cloud Server 2.3.1.3 Doctor 2.4 Data Classification 2.4.1 Access Control 2.4.2 Content 2.4.3 Storage 2.4.4 Soft Computing Techniques for Data Classification 2.5 Related Work 2.6 Conclusion References 3 Research Challenges in Pre-Copy Virtual Machine Migration in Cloud Environment 3.1 Introduction 3.1.1 Cloud Computing 3.1.1.1 Cloud Service Provider 3.1.1.2 Data Storage and Security 3.1.2 Virtualization 3.1.2.1 Virtualization Terminology 3.1.3 Approach to Virtualization 3.1.4 Processor Issues 3.1.5 Memory Management 3.1.6 Benefits of Virtualization 3.1.7 Virtual Machine Migration 3.1.7.1 Pre-Copy 3.1.7.2 Post-Copy 3.1.7.3 Stop and Copy 3.2 Existing Technology and Its Review 3.3 Research Design 3.3.1 Basic Overview of VM Pre-Copy Live Migration 3.3.2 Improved Pre-Copy Approach 3.3.3 Time Series–Based Pre-Copy Approach 3.3.4 Memory-Bound Pre-Copy Live Migration 3.3.5 Three-Phase Optimization Method (TPO) 3.3.6 Multiphase Pre-Copy Strategy 3.4 Results 3.4.1 Finding 3.5 Discussion 3.5.1 Limitation 3.5.2 Future Scope 3.6 Conclusion References 4 Estimation and Analysis of Prediction Rate of Pre-Trained Deep Learning Network in Classification of Brain Tumor MRI Images 4.1 Introduction 4.2 Classes of Brain Tumors 4.3 Literature Survey 4.4 Methodology 4.5 Conclusion References 5 An Intelligent Healthcare Monitoring System for Coma Patients 5.1 Introduction 5.2 Related Works 5.3 Materials and Methods 5.3.1 Existing System 5.3.2 Proposed System 5.3.3 Working 5.3.4 Module Description 5.3.4.1 Pulse Sensor 5.3.4.2 Temperature Sensor 5.3.4.3 Spirometer 5.3.4.4 OpenCV (Open Source Computer Vision) 5.3.4.5 Raspberry Pi 5.3.4.6 USB Camera 5.3.4.7 AVR Module 5.3.4.8 Power Supply 5.3.4.9 USB to TTL Converter 5.3.4.10 EEG of Comatose Patients 5.4 Results and Discussion 5.5 Conclusion References 6 Deep Learning Interpretation of Biomedical Data 6.1 Introduction 6.2 Deep Learning Models 6.2.1 Recurrent Neural Networks 6.2.2 LSTM/GRU Networks 6.2.3 Convolutional Neural Networks 6.2.4 Deep Belief Networks 6.2.5 Deep Stacking Networks 6.3 Interpretation of Deep Learning With Biomedical Data 6.4 Conclusion References 7 Evolution of Electronic Health Records 7.1 Introduction 7.2 Traditional Paper Method 7.3 IoMT 7.4 Telemedicine and IoMT 7.4.1 Advantages of Telemedicine 7.4.2 Drawbacks 7.4.3 IoMT Advantages with Telemedicine 7.4.4 Limitations of IoMT With Telemedicine 7.5 Cyber Security 7.6 Materials and Methods 7.6.1 General Method 7.6.2 Data Security 7.7 Literature Review 7.8 Applications of Electronic Health Records 7.8.1 Clinical Research 7.8.1.1 Introduction 7.8.1.2 Data Significance and Evaluation 7.8.1.3 Conclusion 7.8.2 Diagnosis and Monitoring 7.8.2.1 Introduction 7.8.2.2 Contributions 7.8.2.3 Applications 7.8.3 Track Medical Progression 7.8.3.1 Introduction 7.8.3.2 Method Used 7.8.3.3 Conclusion 7.8.4 Wearable Devices 7.8.4.1 Introduction 7.8.4.2 Proposed Method 7.8.4.3 Conclusion 7.9 Results and Discussion 7.10 Challenges Ahead 7.11 Conclusion References 8 Architecture of IoMT in Healthcare 8.1 Introduction 8.1.1 On-Body Segment 8.1.2 In-Home Segment 8.1.3 Network Segment Layer 8.1.4 In-Clinic Segment 8.1.5 In-Hospital Segment 8.1.6 Future of IoMT? 8.2 Preferences of the Internet of Things 8.2.1 Cost Decrease 8.2.2 Proficiency and Efficiency 8.2.3 Business Openings 8.2.4 Client Experience 8.2.5 Portability and Nimbleness 8.3 IoMT Progress in COVID-19 Situations: Presentation 8.3.1 The IoMT Environment 8.3.2 IoMT Pandemic Alleviation Design 8.3.3 Man-Made Consciousness and Large Information Innovation in IoMT 8.4 Major Applications of IoMT References 9 Performance Assessment of IoMT Services and Protocols 9.1 Introduction 9.2 IoMT Architecture and Platform 9.2.1 Architecture 9.2.2 Devices Integration Layer 9.3 Types of Protocols 9.3.1 Internet Protocol for Medical IoT Smart Devices 9.3.1.1 HTTP 9.3.1.2 Message Queue Telemetry Transport (MQTT) 9.3.1.3 Constrained Application Protocol (CoAP) 9.3.1.4 AMQP: Advanced Message Queuing Protocol (AMQP) 9.3.1.5 Extensible Message and Presence Protocol (XMPP) 9.3.1.6 DDS 9.4 Testing Process in IoMT 9.5 Issues and Challenges 9.6 Conclusion References 10 Performance Evaluation of Wearable IoT-Enabled Mesh Network for Rural Health Monitoring 10.1 Introduction 10.2 Proposed System Framework 10.2.1 System Description 10.2.2 Health Monitoring Center 10.2.2.1 Body Sensor 10.2.2.2 Wireless Sensor Coordinator/Transceiver 10.2.2.3 Ontology Information Center 10.2.2.4 Mesh Backbone-Placement and Routing 10.3 Experimental Evaluation 10.4 Performance Evaluation 10.4.1 Energy Consumption 10.4.2 Survival Rate 10.4.3 End-to-End Delay 10.5 Conclusion References 11 Management of Diabetes Mellitus (DM) for Children and Adults Based on Internet of Things (IoT) 11.1 Introduction 11.1.1 Prevalence 11.1.2 Management of Diabetes 11.1.3 Blood Glucose Monitoring 11.1.4 Continuous Glucose Monitors 11.1.5 Minimally Invasive Glucose Monitors 11.1.6 Non-Invasive Glucose Monitors 11.1.7 Existing System 11.2 Materials and Methods 11.2.1 Artificial Neural Network 11.2.2 Data Acquisition 11.2.3 Histogram Calculation 11.2.4 IoT Cloud Computing 11.2.5 Proposed System 11.2.6 Advantages 11.2.7 Disadvantages 11.2.8 Applications 11.2.9 Arduino Pro Mini 11.2.10 LM78XX 11.2.11 MAX30100 11.2.12 LM35 Temperature Sensors 11.3 Results and Discussion 11.4 Summary 11.5 Conclusion References 12 Wearable Health Monitoring Systems Using IoMT 12.1 Introduction 12.2 IoMT in Developing Wearable Health Surveillance System 12.2.1 A Wearable Health Monitoring System with Multi-Parameters 12.2.2 Wearable Input Device for Smart Glasses Based on a Wristband-Type Motion-Aware Touch Panel 12.2.3 Smart Belt: A Wearable Device for Managing Abdominal Obesity 12.2.4 Smart Bracelets: Automating the Personal Safety Using Wearable Smart Jewelry 12.3 Vital Parameters That Can Be Monitored Using Wearable Devices 12.3.1 Electrocardiogram 12.3.2 Heart Rate 12.3.3 Blood Pressure 12.3.4 Respiration Rate 12.3.5 Blood Oxygen Saturation 12.3.6 Blood Glucose 12.3.7 Skin Perspiration 12.3.8 Capnography 12.3.9 Body Temperature 12.4 Challenges Faced in Customizing Wearable Devices 12.4.1 Data Privacy 12.4.2 Data Exchange 12.4.3 Availability of Resources 12.4.4 Storage Capacity 12.4.5 Modeling the Relationship Between Acquired Measurement and Diseases 12.4.6 Real-Time Processing 12.4.7 Intelligence in Medical Care 12.5 Conclusion References 13 Future of Healthcare: Biomedical Big Data Analysis and IoMT 13.1 Introduction 13.2 Big Data and IoT in the Healthcare Industry 13.3 Biomedical Big Data Types 13.3.1 Electronic Health Records 13.3.2 Administrative and Claims Data 13.3.3 International Patient Disease Registries 13.3.4 National Health Surveys 13.3.5 Clinical Research and Trials Data 13.4 Biomedical Data Acquisition Using IoT 13.4.1 Wearable Sensor Suit 13.4.2 Smartphones 13.4.3 Smart Watches 13.5 Biomedical Data Management Using IoT 13.5.1 Apache Spark Framework 13.5.2 MapReduce 13.5.3 Apache Hadoop 13.5.4 Clustering Algorithms 13.5.5 K-Means Clustering 13.5.6 Fuzzy C-Means Clustering 13.5.7 DBSCAN 13.6 Impact of Big Data and IoMT in Healthcare 13.7 Discussions and Conclusions References 14 Medical Data Security Using Blockchain With Soft Computing Techniques: A Review 14.1 Introduction 14.2 Blockchain 14.2.1 Blockchain Architecture 14.2.2 Types of Blockchain Architecture 14.2.3 Blockchain Applications 14.2.4 General Applications of the Blockchain 14.3 Blockchain as a Decentralized Security Framework 14.3.1 Characteristics of Blockchain 14.3.2 Limitations of Blockchain Technology 14.4 Existing Healthcare Data Predictive Analytics Using Soft Computing Techniques in Data Science 14.4.1 Data Science in Healthcare 14.5 Literature Review: Medical Data Security in Cloud Storage 14.6 Conclusion References 15 Electronic Health Records: A Transitional View 15.1 Introduction 15.2 Ancient Medical Record, 1600 BC 15.3 Greek Medical Record 15.4 Islamic Medical Record 15.5 European Civilization 15.6 Swedish Health Record System 15.7 French and German Contributions 15.8 American Descriptions 15.9 Beginning of Electronic Health Recording 15.10 Conclusion References Index Also of Interest