Intelligent Healthcare : Applications of AI in EHealth

This book fosters a scientific debate for sophisticated approaches and cognitive technologies (such as deep learning, machine learning and advanced analytics) for enhanced healthcare services in light of the tremendous scope in the future of intelligent systems for healthcare. The authors discuss the proliferation of huge data sources (e.g. genomes, electronic health records (EHRs), mobile diagnostics, and wearable devices) and breakthroughs in artificial intelligence applications, which have unlocked the doors for diagnosing and treating multitudes of rare diseases. The contributors show how the widespread adoption of intelligent health based systems could help overcome challenges, such as shortages of staff and supplies, accessibility barriers, lack of awareness on certain health issues, identification of patient needs, and early detection and diagnosis of illnesses. This book is a small yet significant step towards exploring recent advances, disseminating state-of-the-art techniques and deploying novel technologies in intelligent healthcare services and applications. Describes the advances of computing methodologies for life and medical science data; Presents applications of artificial intelligence in healthcare along with case studies and datasets; Provides an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians. Preface Acknowledgment Contents A Healthcare-Based Intelligent Monitoring Paradigm in Quantum Dot Cellular Automata (QCA) to Protect Against Novel Corona Outbreak 1 Introduction 2 Background QCA Concept Associative Memory Computation CAM Approach Towards Confinement of Associative Memory 3 QCA Circuits Fundamental Gates Memory Cell Structures Five-Input Minority Gate Five-Input Minority Gate-Based Multilayer CAM Cell 4 Scope 5 Proposed Paradigm of Healthcare Monitoring 6 Entire Operation for Process Flow of Implemented Design in Quantum Dot Cellular Automata (QCA) Nanotechnology 7 Results 8 Conclusion References Intelligent Healthcare 1 Introduction 2 Research Method 3 Labelling or Classification of Vital-Sign Data Existing One-Class Classification (OCC) Methods Existing Two-Class Classification (TCC) Methods 4 Results Graphical Analysis of Measurement of Systolic, Diastolic and Pulse Rate Parameters 5 Discussion 6 Conclusion References Big Data 1 Introduction 2 Recommendation System and Its Basic Concepts Phases of Recommendation System Information Collection Phase Methodism 3 Health Recommendation System Designing the Health Recommendation System Framework for HRS Methods to Design HRS Evaluation of HRS 4 Proposed Intelligent-Based HRS Big Data Analytics and Intelligence Healthcare Perspectives Architectural Outline Designed for Big Data Analytics in Health Care 5 Intelligence-Based Health Approval Classification via Big Data Analytics 6 Enhancing Workflows in Healthcare 7 Healthcare Knowledge Bases Making Better Doctors Optimization Diagnosing Disease Drug Discovery 3D Printing Bioprinting and Tissue Engineering Drug and Facilities Gene Care The Virtual and Growing Reality Health Treatment and Delivery Internet and Classroom Meetings Logging In Supply Chain Verification Entry to Medical Record Robot Movement Surgery with Robotic Aid Drones Intelligent Locations Hospitals Intelligent 8 Advantages and Disadvantages of the Proposed Health Recommendation System Using Big Data Analytics 9 Conclusion and Future Research References Implication of Statistical Methods on Patient Data: An Approach for Cancer Survivability Prediction 1 Introduction 2 Cancer Statistics Breast Cancer Ovarian Cancer 3 Basics of Survival Analysis Censoring Hazard Function Linear Regression and Its Limitations 4 Popular Survival Analysis Method Kaplan-Meier Log-Rank Test Cox Regression Random Forest Model 5 Result and Discussion Data Preparation Survival Analysis Using Kaplan-Meier (KM) Survival Analysis Using Cox Regression 6 Conclusion References Machine Learning with IoT and Big Data in Healthcare 1 Introduction 2 Background 3 Machine Learning Application Areas of Machine Learning in Intelligent Healthcare Advantages of Machine Learning 4 Big Data in Healthcare Big Data Characteristics for Intelligent Healthcare Stages of Big Data Analytics 5 IoT in Healthcare IoT Application Areas in Healthcare IoT Offers Following Advantages in Healthcare 6 Challenges 7 Solutions and Recommendations 8 Future Work 9 Conclusion References Modelling Covid-19: Transmission Dynamics Using Machine Learning Techniques 1 Background 2 Objective 3 Methodology 4 Results 5 Conclusion References An Innovative Pandemic Knowledgebase Using Machine Learning 1 Introduction 2 Historical Analysis of Epidemic and Pandemic 3 COVID – 19: Pandemic 4 Data Analytics and Knowledgebase 5 Novel Case Studies International National 6 Rule-Based Learning in Healthcare Using Pandemic Knowledgebase 7 Conclusion References Reviewing Classification Methods on Health Care 1 Introduction to Supervised Learning Different Supervised Learning Methods Comparative Summary of Supervised Methods 2 Applications of Supervised Learning in Healthcare 3 Healthcare Datasets Used in the Study 4 Classification Metrics 5 Methodology 6 Results and Analysis 7 Conclusion and Future Work References Predicting and Managing Glycemia Levels Using Advanced Time Series Forecasting Methods 1 Introduction 2 Background Study Defining Time Series and Related Terms Various Researchers' Study on Time Series Analysis for Diabetes 3 Methodology Augmented Dickey–Fuller Test ACF and PACF Plots Techniques Applied for Time Series Analysis ARIMAX fbProphet Forecasting Evaluation Using Mean Absolute Error (MAE) 4 Experiment Results and Analysis Data Extraction Data Preparation ARIMAX Model Training ADF ACF and PACF Prophet Model Forecasting Model Interpreting the Results 5 Conclusion and Future Trends References Machine Learning Applications in Anti-cancer Drug Discovery 1 Introduction 2 Background Drug Repurposing Cancer Classification Drug Synergy Prediction 3 Research Gaps in Computational Drug Discovery 4 Future of Computational Drug Discovery Deep Learning for Drug Discovery Role of Deep Learning in Cancer Classification Role of Deep Learning in MicroRNA Analysis in NGS 5 Conclusion and Future Directions References Deep Learning in Healthcare 1 Introduction 2 Deep Convolution Neural Network (CNNs) in Healthcare 3 Deep Learning for Genomics 4 Deep Learning in Medicine Electronic Health Record Data ICD-10 Codes Probabilistic Diagnoses with Bayesian Networks 5 Machine Learning for Microscopy Deterministic Super-Resolution Microscopy Stochastic Super-Resolution Microscopy 6 Natural Language Processing in Healthcare 7 Prediction Using EHR 8 Deep Learning Support in Healthcare 9 Applications of ML in Healthcare 10 Applications of ML in Clinical Workflows 11 Secure, Private, and Robust ML for Healthcare Solutions Data Protection-ML: ML 12 Conclusion References Self-Organized Deep Learning: A Novel Step to Fight Against Severe Acute Respiratory Syndrome 1 Introduction Overall Theme 2 Background Contextual Feature of the Book Chapter Need of Telemedicine for COVID-19 Previous Work 3 Working of Proposed Model 4 Deep Analysis 5 Conclusion References Clustering Algorithms in Healthcare 1 Introduction 2 Clustering K-Means Clustering K-Means Clustering Algorithm Mean-Shift Clustering Algorithm DBSCAN Clustering Expectation-Maximization (EM) Clustering Using Gaussian Mixture Models (GMM) Hierarchical Agglomerative Clustering 3 Experimental Analysis Performance Analysis 4 Conclusions References Multimodal Detection of COVID-19 Fake News and Public Behavior Analysis—Machine Learning Prospective 1 Introduction 2 Related Works 3 About COVID-19 Fake News 4 Methodology Multimodal Classifiers (MC) Support Vector Machines (SVM) Stochastic Gradient Descent (SGD) Gradient Boosting (GB) Bounded Decision Trees (BDT) Random Forests (RF) 5 Implementation Results 6 Conclusion 7 Future Scope References A Review of Machine Learning Approaches in Clinical Healthcare 1 Introduction 2 Applied Machine Learning in Healthcare 3 The Ethics of Using Algorithms in Healthcare 4 Current Machine Learning Healthcare Applications 5 Machine Learning Algorithms 6 Future Possibilities in General Practice 7 Challenges Risks/Threats 8 Conclusion References Coronavirus Pandemic: A Review of a New-fangledRisk to Public Health 1 Introduction 2 Virion Structure 3 Objective 4 Methodology of Review 5 Epidemiology of COVID-19 6 Total Coronavirus Cases 7 Transmission 8 Diagnosis 9 Prevention of Transmission 10 Quarantine 11 Treatment 12 Application of Nanotechnology to Combat Against Coronavirus Diagnosis and Treatment of CoV by Nanomaterials Nanomaterials for Facemasks Production Nanomaterials for Disinfectants Anti-COVID-19 Nanocoating 13 Conclusions References Impact of COVID-19 Pandemic on Obese and Asthma Patients: A Systematic Review 1 Introduction 2 Conjunction of COVID-19 and Asthma Effects of COVID-19 in Asthma Patients Symptoms of COVID-19 in Asthma Patients Precautions and Measures to Be Taken by Asthma Patients Against COVID-19 3 A Conjunction of COVID-19 and Obesity Effects of COVID-19 in Obese Patients Symptoms of COVID-19 in Obese Patients Precautions and Measures to Be Taken by Obese Patients Against COVID-19 4 Conclusion References Case Study on COVID-19 Scenario over HighlyAffected States of India 1 Introduction 2 Specific Healthcare Problems/Difficulties in Indian States Healthcare Facilities and Challenges in Maharashtra to Take Care of COVID-19 Scenario in Maharashtra Healthcare Facilities and Challenges in Tamil Nadu to Take Care of COVID-19 Scenario Healthcare Facilities and Challenges in Delhi to Take Care of COVID-19 Scenario Healthcare Facilities and Challenges in Gujarat to Take Care of COVID-19 Scenario Healthcare Facilities and Challenges in Rajasthan to Take Care of COVID-19 Scenario Other Measures to Control Spread of COVID-19 3 Challenges in Controlling COVID-19 Cases Reasons and Challenges for Large Number of COVID-19 Cases in Mumbai, Maharashtra Reasons and Challenges for Large Number of COVID-19 Cases in Tamil Nadu Reasons and Challenges for Large Number of COVID-19 Cases in Gujarat Reasons for Large Number of COVID-19 Cases in Delhi Reasons for Large Number of COVID-19 Cases in Uttar Pradesh Reasons for Large Number of COVID-19 Cases in Rajasthan 4 Use of Technology to Handle Challenges During COVID-19 in India Technological Challenges During COVID-19 Heavy Load on Internet Information Technology Distance Teaching-Learning Impact of COVID on Frontline Workers in India COVID Cases Forecasting 5 Architectural Design and Planning Challenges Related to COVID-19 Planning Aspects for Slums Related to COVID-19 Planning Aspects for Buildings Related to COVID-19 6 Conclusion References Index