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.
Author(s): Surbhi Bhatia, Ashutosh Kumar Dubey, Rita Chhikara, Poonam Chaudhary, Abhishek Kumar
Series: EAI/Springer Innovations in Communication and Computing
Publisher: Springer
Year: 2021
Language: English
Pages: 335
City: Singapore
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
