Translating Healthcare Through Intelligent Computational Methods

Description

This book provides information on interdependencies of medicine and telecommunications engineering and how Covid exemplifies how the two must rely on each other to effectively function in this era. The book discusses new techniques for medical service improvisation such as clear cut views on medical technologies. The authors provide chapters on processing of medical amenities using medical images, the importance of data and information technology in medicine, and machine learning and artificial intelligence in healthcare. Authors include researchers, academics, and professionals in the field of communications engineering with a variety of perspectives.  Preface Acknowledgement Contents About the Editors Part I: Introduction Introduction to Translating Healthcare Through Intelligent Computational Methods 1 Introduction 1.1 Role of Technology in Healthcare 1.1.1 Electronic Health Records 1.1.2 Telehealth 1.1.3 Personalized Treatment and Surgical Technology 1.2 Primary Healthcare 1.3 Secondary Healthcare 1.4 Tertiary Healthcare 1.5 Quaternary Healthcare 2 Problems Faced in Utilizing Healthcare 3 Intelligent Computational Methods 4 Healthcare Through Intelligent Computational Methods 4.1 Healthcare Approaches Using Deep Learning 4.1.1 Data Analytics 4.1.2 Chatbots for Mental Health 4.1.3 Personalized Medical Treatments 4.1.4 Response to Patient Queries 4.1.5 Prescription Audit 4.1.6 Health Insurance 4.1.7 Research and Development 4.2 Intelligent Systems and Computational Methods in Medical and Healthcare 4.2.1 Role of AI in Healthcare 4.2.2 Virtual Nursing Assistants 4.2.3 Wearable Technology and Robotics 4.2.4 Data Management and Diagnostics 4.2.5 Healthcare Industry Services 5 Conclusion References Healthcare Administration and Management in Current Scenario 1 Introduction 2 Attributes of Hospital Management 3 Human Resources Management 3.1 HRM in the Hospital Industry 3.2 The Importance of Human Resources in the Healthcare Sector 4 Recruitment and Selection in the Healthcare Sector 4.1 Recruitment and Selection Issues Faced in the Industry Recently 4.2 Hard Versus Soft Skills 4.3 Psychometric Testing in the Selection Process 5 Importance of Training in the Healthcare Sector 5.1 Training Healthcare Teams Online 5.2 Benefits of Managing Training Online 5.3 Eliminating the Skill Shortage Gap 5.4 Excellent Form of Continuing Education 5.5 Ease of Communication 5.6 Better Versatility for Both HR and Hospital Staff 5.7 Online Training Can Also Assist Employees 6 The Importance of Performance Management in Healthcare Sector 6.1 Top Performance Challenges Faced in the Health Industry 6.2 Performance Management: A Tool to Build High Performing Workforce 7 Compensation and Retention Strategies for Healthcare Sector 7.1 Build Up a Compensation Strategy for Executive Talent 7.1.1 Base Salary 7.1.2 Momentary Incentives 7.2 Long-Haul Incentives 7.2.1 Maintenance Incentives 7.3 Plan and Implement an Effective Compensation Strategy 8 Hospital Information System 8.1 Potential Advantages of Hospital Information Systems 8.2 Safety and Quality of Healthcare 8.3 Standards and Accreditation 9 Biggest Issues Facing Healthcare Today 9.1 Challenges, Obligations and Opportunities 9.2 Turning Challenges into Opportunities 10 Conclusion References Part II: Unease of Conventional Medicine An Insight into Traditional and Integrative Medicine 1 Introduction 2 Indian Traditional Medicine 2.1 Ayurveda 2.2 Yoga 2.3 Medical Yoga 2.4 Unani 2.5 Siddha 2.6 Homeopathy 3 Chinese Traditional Medicine 3.1 Acupuncture 3.2 Tai Chi 3.3 Chinese Herbalism 4 African Traditional Medicine 5 Korean Traditional Medicine 6 European Traditional Medicine 7 Arabic Traditional Medicine 8 Osteopathic Medicine 9 Alternative Medicine Versus Conventional Medicine 10 Conclusion References Heart Disease Prediction Desktop Application Using Supervised Learning 1 Introduction 2 Related Works 3 Methodology 3.1 K-Nearest Neighbor 3.2 Support Vector Machine 3.3 Random Forest 4 Experimental Evaluation 4.1 Evaluation Metrics 4.2 Live Heart Disease Prediction Module 5 Results and Discussions 6 Conclusion and Future Work References Part III: Mutating Medicine Using Artificial Intelligence (AI) Healthcare Revolution and Integration of Artificial Intelligence 1 Introduction 1.1 Healthcare Revolution in the Past Century 1.2 Artificial Intelligence: A Transformation in Healthcare Delivery 2 Artificial Intelligence in Healthcare 2.1 Components of Artificial Intelligence 2.1.1 Machine Learning 2.1.2 Computational Intelligence 2.1.3 Deep Learning 2.1.4 Natural Language Processing 2.1.5 Cognitive Computing 2.1.6 Computer Vision 3 Impact of AI in Medicine 3.1 AI and Traditional Medicine: Combining Impact 3.2 Future Role of Physicians 3.3 Explainable AI 3.4 Risks and Safety Challenges 4 Conclusion References Logistic Regression-Based Machine Learning Model for Mutation Classification in the Discovery of Precision Medicine 1 Introduction 2 Literature Survey 3 Logistic Regression 4 Logistic Regression on Mutation Classification 5 Logistic Regression-Based Model for Mutation Dataset 6 Experimental Analysis 7 Conclusion References Part IV: Evolution of Healthcare Techniques (Prognosis and Diagnosis) The Revolution in Progressive Healthcare Techniques 1 Introduction 2 Evolution of Primary Healthcare 2.1 Community Participation 2.2 Inter-sectoral Coordination 2.3 Appropriate Technology 2.4 Support Mechanism Made Available 3 Teleological Healthcare Systems 4 Artificial Intelligence in Healthcare 5 Machine Learning Prediction in Healthcare 5.1 Identification of Disease 6 IoT in Health Informatics 7 Wave of Wearables in Clinical Management 8 Direct to Consumer 8.1 Cardiology 8.2 Bariatric Medicine 8.3 Endocrinology 9 Devices Used or Managed by Clinicians 9.1 Cardiology 9.2 Dermatology 9.3 Neurology and Psychiatry 9.4 Pulmonology and Sleep Medicine 9.5 Surgery 10 Role of Big Data in Healthcare 10.1 Big Data in Health Records 10.2 Deriving Big Data from Omic Studies 11 Conclusion References Epocalypse Telepathy of Objects Using Brain Force 1 Introduction 1.1 Benefits 2 Materials and Methods 2.1 Construction 2.2 Discussion 2.3 Article Highlights 3 Simulation Results 4 Conclusion References Automatic Hybrid Deep Learning Network for Image Lesion Prognosis and Diagnosis 1 Introduction 2 Objectives 3 Methods 4 Proposed Work 5 Results References Comparison of Cardiac Stroke Prediction and Classification Using Machine Learning Algorithms 1 Introduction 2 Literature Review 3 Proposed Method 3.1 Data Flow Diagram 3.2 UML Diagrams 3.3 Sequence Diagram 4 System Implementation 4.1 Data Collection 4.2 Data Preparation 4.3 Model Selection 4.4 Collaboration Diagram 5 Analysis and Prediction Results of HRFLM 5.1 Parameters used for analysis 5.2 Simulation Model for Prediction of the Disorder 6 Conclusion References Technologies and Therapies for Disease Diagnosis and Treatment 1 Introduction 2 Defence Systems of the Human Body 2.1 Non-specific Immune Response 2.2 Specific Immune Response 3 Vital Signs of the Body 4 Molecular Techniques for Disease Detection 4.1 Polymerase Chain Reaction 4.2 Next-Generation Sequencing 4.3 Blotting 4.4 DNA Microarrays 5 Biopotential Measurement Techniques 5.1 Electromyography 5.2 Electrocardiography 5.3 Electroencephalography 5.4 Electrooculography 6 Imaging Techniques 6.1 Radiography 6.2 Computed Tomography 6.3 Magnetic Resonance Imaging 6.4 Positron Emission Tomography 6.5 Thermal Imaging 6.5.1 IR Equipment 6.5.2 Other Applications of Thermography 6.5.3 Other Imaging Modalities 7 Therapeutic Products in Healthcare 7.1 Phytocompounds 7.2 Antibiotics 7.3 Monoclonal Antibodies 7.4 Interferons 7.5 Vaccines 8 Conclusion References Part V: Evolution of Healthcare Techniques (Therapy) Evaluating the Impacts of Healthcare Interventions 1 Introduction 2 Bioethics 2.1 Reason and Extension 2.2 Standards 3 Genetic Counseling and Research 3.1 Variety in Hereditary Examination is Critical 4 Involvement of Patient or Public in Healthcare System 4.1 Benefits and Consequences of Patient Participation in Healthcare 4.2 Public Involvement Policies 4.3 Current Policies to Encourage Public Involvement 5 Epidemiological Evolution 5.1 Types of Epidemiology 6 Assessment of Matrix 6.1 Utilization of an Evaluation Matrix During Every Assessment Stage 6.1.1 Stage 1: Planning 6.1.2 Stage 2: Preparation 6.1.3 Stage 3: Inception 6.1.4 Stage 4: Data Collection 6.1.5 Stage 5: Data Analysis and Reporting 7 Conclusion References Hemodynamic Analysis of Bifurcated Artery Using Computational Fluid Dynamics 1 Introduction 1.1 Blood as the Fluid 1.2 Geometry Preparation 1.3 Meshing 1.4 Physics Setup 1.5 Fluid Mechanics of Blood Flow 2 Contour Analysis 2.1 Velocity Streamline and Pressure Contour 2.2 Hemodynamic Characteristics 2.2.1 Blood Flow Velocities Analysis 2.2.2 Wall Shear Stress Analysis 2.2.3 Arterial Damage 3 Conclusion References Therapeutic Equipment and Its Enhancement via Computational Techniques 1 Introduction 2 Therapeutics 3 Therapeutics Devices 4 Types of Therapeutic Tools 5 Therapeutic Treatments 6 Preventive Medicine 7 Treatment of Symptoms 7.1 Pain 7.2 Nausea and vomiting 7.3 Diarrhea 7.4 Cough 7.5 Insomnia 8 Various Therapeutic Devices 8.1 Pacemaker 8.1.1 What a Pacemaker Ensures? 8.1.2 How Does a Pacemaker Function? 8.2 Defibrillator 8.2.1 Defibrillation 8.2.2 Defibrillator Applications 8.3 Ventilators 8.3.1 Function of Ventilators 8.3.2 Ventilators and COVID-19 8.3.3 Ventilators During Surgery 8.4 Diathermy 8.4.1 Types of Diathermy 8.4.2 How Does Diathermy Work? 8.4.3 Advantages of Diathermy 8.5 Dialyzer 8.5.1 Hemodialysis 8.5.2 Peritoneal Dialysis 9 Challenges in Therapeutic Devices and Procedures 10 Computer-Assisted Therapy 11 Conclusion References Part VI: Novelty in Emerging Soft Computation Emerging Techniques and Algorithms Used in Soft Computation 1 Introduction 2 Emerging Techniques in Soft Computing 2.1 Fuzzy Computing 2.2 Neural Network 2.2.1 Perceptron 2.2.2 Probabilistic Neural Network 2.3 Genetic Algorithm 2.4 Associative Memory 2.4.1 Auto-associative Memory 2.4.2 Hetero-associative Memory 2.4.3 Working of Associative Memory 2.5 Adaptive Resonance Theory 2.5.1 Basics of ART Architecture 2.6 Classification 2.7 Clustering 2.8 Probabilistic Reasoning 2.9 Bayesian Network 3 Application Areas of Soft Computing 3.1 Agricultural Machinery 3.2 Biomedical Engineering 3.3 Consumer Electronics 3.4 Decision Support 3.5 Intelligent Agents 3.6 Nano and Micro Systems 3.7 Robotics 4 Conclusion References Emerging Soft Computation Tools for Skin Cancer Diagnostics 1 Introduction 2 Analogous Performance 3 Evaluation of Skin Malignancy Using Machine-Learning Methodologies 3.1 Anisotropic Diffusion Filtering 3.2 Melanoma Segmentation Analysis 3.3 Feature Extraction 3.4 Benign and Malignant Classification 3.5 K-Nearest Neighbor 3.6 Support Vector Machine 3.7 Decision Tree 3.8 Multilayer Perceptron 3.9 Random Forest 3.10 Summary of Melanoma Classification Using Machine Learning 4 Deep-Learning Approaches to Skin Cancer Diagnosis 4.1 Image Enhancement 4.2 Augmentation of Images 4.3 AlexNet Topology 4.4 Experimental Findings 5 Conclusion References Part VII: Precise Healthcare Technologies Serving in Cancer Research Advanced Sustainable Technological Developments for Better Cancer Treatments 1 Introduction 2 Early Diagnosis 2.1 Screening 2.2 Cancer Effective Treatment 2.2.1 Palliative Care 2.3 Types of Treatments of Cancer 2.3.1 Biomarker Testing System for Cancer Treatment 2.3.2 Biomarkers’ Uses for Targeted Therapies 3 Transcriptomic, Proteomic, and Metabolomic Techniques 3.1 Transcriptomics 3.2 Comparative Transcriptomics Analysis 3.3 Proteomics 3.4 Precision Medicine 4 Conclusion References Healthcare Technologies Serving Cancer Diagnosis and Treatment 1 Introduction 1.1 Breast Cancer 1.2 Lung Cancer 2 Imaging Modalities for Cancer Screening and Detection 2.1 Imaging Modalities 2.2 Cancer Screening and Diagnosis Techniques 2.3 Lung Cancer Detection Using CT Scan Images 3 Cancer Prediction and Detection with Data Analysis 3.1 Cancer Analysis Using Neural Networks 4 Conclusion References Therapy and Diagnosis of Cancer Techniques: A Review 1 Introduction 1.1 Outline of Artificial Intelligence 1.2 Introduction to Cancer 1.3 Differences Between Cancer Cells and Normal Cells 2 Goals of AI 3 Interconnection of AI with Other Disciplines 4 Techniques Used in Cancer Diagnosis and Therapy 4.1 Nanomedicine 4.2 Magnetic Resonance Imaging 4.3 Photoacoustic Imaging 4.4 Positron Emission Tomography Imaging 4.5 Chemotherapy 4.6 Phases of Cancer Diagnosis and Therapy 4.7 Prediction of Cancer Cells Using AI Techniques 4.7.1 Image Acquisition 4.7.2 Pre-processing 4.7.3 Feature Extraction 4.7.4 Classification 5 Other AI Techniques for Cancer Diagnosis and Therapy 5.1 k-Means Algorithm 5.2 Fuzzy c-Means Algorithm 5.3 Wavelet Analysis 6 Implementation and Results 6.1 Decision Tree 6.2 ANN Classifier 7 Discussion 8 Conclusion References Robust Intelligent Multimodal Biometric Authentication Systems for a Secured EHR 1 Introduction 2 EHR Biometric Modules 3 PIC Microcontroller Module 3.1 PIC18F4520 Flash 40-Pin 32kB 40 MHz Microcontroller (Microchip) Specification 3.2 Features of Power Management 3.3 Internal Oscillator Block 4 Finger Print Module 4.1 Finger Print Sensor 4.2 Fingerprint Sensor Type and Its Specifications 4.3 Inputs and Outputs of Fingerprint Sensor 4.3.1 Input: Two Ways to Trigger the Function of Fingerprint Sensor 4.3.2 Outputs (Response) 4.4 Types of Function 4.4.1 Add (Enroll) Function 4.4.2 Search Function 4.4.3 Empty Function 5 Voice Recognition Module 5.1 Voice Recognition 5.2 Parameters 6 Physiological Sensors Module 6.1 Role of Sensor Module 6.2 Temperature Sensor 6.3 ECG Sensor 6.4 Pressure Sensor 6.4.1 Various Modes of Pressure Measurements 7 Compiler Module 7.1 CCS Compiler for PIC Microcontroller Software 7.2 Key Features of Compiler Module 7.3 Pro Level Optimization 7.4 Optimization of Strings 7.5 Efficient Data Structures Mapped into Program Memory 7.6 Additional Features 7.7 PIC KIT3 for Programmer 7.8 Features 8 Conclusion References Prognosis and Diagnosis of Cancer Using Robotic Process Automation 1 Introduction 2 Related Work 3 Need for Robotic Process Automation in Health Care 4 RPA Workflow 5 Methodologies 5.1 Prepare RPA 5.2 RPA Solution Design 5.3 RPA Build and Test 5.4 Stabilize RPA and Constant Improvement 6 Conclusion References Part VIII: Telecommunication with Improved Intelligence in Medicine Remote Delivery of Healthcare Services 1 Introduction 2 Block Diagram of Telemedicine 3 Delivery Modes of Telemedicine 4 Technology Used in Telemedicine 4.1 HL7 (Health Level 7) 4.2 Transmission of Images 4.2.1 Standards for Still Images 4.3 Transmission of Video 4.4 Transmission of Audio 5 Wireless Technology for Telemedicine 5.1 Wi-Fi 5.2 WiMax 5.3 Bluetooth 5.4 Zigbee 5.5 Ultra-Wideband Technology 6 Evolution of Wireless Communication 6.1 Zeroth Generation (0G) 6.2 1G (First Generation) 6.3 2G (Second Generation) 6.4 3G (Third Generation) 6.5 4G (Fourth Generation) 6.6 5G (Fifth Generation) 6.7 6G (Sixth Generation) 7 Mobile Telemedicine Systems 8 Conclusion References Part IX: Future of Medicine and Computational Techniques in Healthcare Future of Medicine in Cognitive Technologies and Automatic Detection via Computational Techniques 1 Introduction 2 Machine Learning in Healthcare 3 Deep Learning in Healthcare 4 Computational Intelligence Used in Healthcare 4.1 Clinical Imaging 4.2 E-Health Records 4.3 Genomics 4.4 Categorizing Brain Tumor Data Using Data Analytic Method Ensemble with Attribute Selection: Case Study 4.5 Automatic Detection of Stress Through AI-Based Wearable Device: Case Study 5 Conclusion References Evolution of Computational Intelligence in Modern Medicine for Health Care Informatics 1 Introduction 2 Precision Medicine 2.1 Detection Methods in Precision Medicine 2.2 Multi-omics/Panomics Analysis 2.3 Omics Data Types 3 Transforming Health Care with Computational Techniques 3.1 Artificial Intelligence 3.1.1 More Efficient Diagnosis of Cancer with AI 3.1.2 EIT Health with McKinsey & Company Workforce 3.1.3 Future of AI in Health Care 3.2 Machine Learning 3.2.1 Usage of Machine Learning’s Natural Learning Program 3.2.2 Future of Machine Learning 3.2.3 Biomedical Screening 3.3 Internet of Things – Health Care Monitoring System 3.3.1 Major Components of Patient Monitoring System 3.3.2 Internet of Things for Patients 3.3.3 Internet of Things for Physicians 3.4 Telemedicine 3.5 Future of Telemedicine in Health Care Management Systems 4 Implication of Big Data in Medical Science 5 The Future of Healthcare – Trends Making an Impact in the Economy 5.1 Virtual Reality in Health Care 5.1.1 The Essential Drivers in VR Acquisition 5.1.2 3D Printing 5.1.3 Surgical Planning 5.1.4 Drug Delivery 6 Conclusion References Covid-19 Diagnosis, Prognosis, and Rehabilitation: Latest Perceptions, Challenges, and Future Directions 1 Introduction 2 Diagnosis Methods for Covid-19 2.1 Virology-Based Methods 2.2 Serology-Based Methods 2.2.1 Lateral Flow Assay 2.2.2 Enzyme-Linked Immunosorbent Assay 2.3 Imaging-Based Methods 2.4 ML Algorithms-Based Methods 2.5 Challenges in Diagnosis Techniques 3 Prognosis Approaches for Covid-19 4 Rehabilitation Approaches for Covid-19 4.1 Challenges in the Recent Studies in Rehabilitation 4.2 Limitations of Current Solutions to Covid-19 5 Conclusion References Part X: Conclusion A Summary of Translating Health Care Through Intelligent Computational Methods 1 Introduction 2 Unease of Conventional Medicine 3 Mutating Medicine Using Intelligence 4 Evolution of Health Care Techniques (Prognosis and Diagnosis) 5 Evolution of Health Care Techniques (Therapy) 6 Novelty in Emerging Soft Computing 7 Precise Health Care Technologies Serving in Cancer Research 8 Telecommunication with Improved Intelligence in Medicine 9 Future of Medicine and Computational Techniques in Health Care References Index