Proceedings of the International Health Informatics Conference: IHIC 2022

Organization
About This Book
Message from the Host Institution
Keynote Talks
Pre-conference Tutorials
Contents
About the Editors
Development of Healthcare System Using Soft Computing Methods
	1 Introduction
	2 Literature Review
	3 Dataset Description
	4 Proposed Work
		4.1 Artificial Neural Networks
		4.2 K-Nearest Neighbor
		4.3 Support Vector Machine
		4.4 Proposed Model
	5 Experimental Results
	6 Conclusion
	References
A Novel Yoga-Based Practice Protocol to Quantify Stress After Performing Attention Task Using Non-invasive Technique
	1 Introduction
		1.1 Clinical Ways to Reduce Stress
		1.2 Non-Clinical Ways to Reduce Stress
	2 Yoga and Stress Management
	3 Methodology
		3.1 Study Design
		3.2 Yoga Practices
		3.3 Participants
		3.4 Data Collection
		3.5 Safety Consideration and Consent Form
	4 Discussion
		4.1 Effect of YBP Using Physiological and Psychological Data
		4.2 Effect of YBP Using Single Modality and Multi-Modality Approach
	5 Conclusion
	References
A Study of Deep Learning Algorithms in Sentiment Analysis of Diverse Domains
	1 Introduction
	2 Sentiment Analysis in Various Domains
		2.1 E-Commerce
		2.2 Emotion Recognition in E-Learning Systems
		2.3 Online Product Review
		2.4 Fake News Detection
		2.5 Student Feedback
	3 Methodology
	4 Discussion
	5 Conclusion
	References
Frequency Allocation in Cognitive Radio Networks
	1 Introduction
	2 Results
		2.1 Probability of Likelihood
		2.2 Probability of Bogus Alert Rate
	3 Explanation
		3.1 Actor Critic Neural Network (ACNN)
		3.2 Actor
		3.3 Critic
		3.4 Krill Herd Optimization
		3.5 Whale Optimization
		3.6 KHWO-ACNN
	4 Conclusions
		4.1 Analysis Using 20 Users
		4.2 Analysis Using 40 Users
	References
An IOT-Based Advanced Health Monitoring System
	1 Introduction
		1.1 Literature Survey
	2 IOT in Healthcare System
	3 Results Obtained
	4 Conclusions and Future Scope
	References
Fault Tolerance in Vehicular Cloud Networks: Link Failure and Malicious Node Detection and Reconfiguration
	1 Introduction
	2 Literature Review
	3 Methodology
		3.1 Design
		3.2 Instrument
		3.3 Data Collection
		3.4 Algorithms
	4 Conclusion and Implications
	References
Multi-filter Enhanced Doctor and Patient Optimization Algorithm for Cancer Diagnosis
	1 Introduction
	2 Background Study
		2.1 Filter-Wrapper-Based FS
		2.2 Doctor and Patient Optimization Algorithm
		2.3 Ensemble Techniques for Individual Filter Output
	3 Proposed Model
	4 Experimental Study
	5 Conclusion
	References
Disease Diagnostic Model Using Fine-Tuned Intensive Learning for Medical Image
	1 Introduction
	2 Related Works
	3 Proposed System
	4 Experimental Results
	5 Conclusion and Future Enhancement
	References
Challenges in Digital Health Care—A Hybrid-Decision Approach Understanding Key Challenges in India
	1 Introduction
		1.1 Research Questions
	2 Research Objectives
	3 Research Methodology
	4 Result Analysis and Discussion
	5 Conclusion
	6 Future Recommendation
	References
Telemedicine and Healthcare Setting for Remote Care of Patients: Status and Future Implications
	1 Introduction
		1.1 TM Adoption
		1.2 Status of TM in India
		1.3 Modalities of Telemedicine
		1.4 Current Application of TM
	2 Challenges of Telemedicine Technology
	3 The Future Aspect of Telemedicine Technology
	4 Conclusion
	References
Performance Evaluation of ML Models in the Health Care Domain to Classify Liver Disease: A Case Study
	1 Introduction
	2 Related Works
	3 Methodology and Experimentation
	4 Results and Discussion
	5 Conclusion
	References
Telemedicine: Enhancing and Reimagining the Public Health in India
	1 Introduction
	2 Telemedicine in India
	3 Telemedicine Guidelines During COVID-19
	4 Literature Review
	5 Research Methodology
	6 Physicians Interview
	7 Results Analysis
	8 Result
	9 Conclusion
	10 Limitations
	References
Effect of Point of Service on Health Department Student’s Creativity in Comprehensive Universities of Ethiopia: Moderating Role of Public-Private Partnership and Mediating Role of Work Place Learning
	1 Introduction
	2 Empirical Literature Review
		2.1 Point of Service in Health Services and Work Place Learning
		2.2 Point of Service, Work Place Learning and Creativity of Students
		2.3 Work Place Learning and Public-Private Partnership
	3 Conceptual Framework
	4 Research Methodology
		4.1 Sampling and Data Collection
	5 Results
		5.1 Reliability and Validity
		5.2 Correlations
		5.3 Fitness of Model
		5.4 Hierarchical Linear Relationship Models
	6 Mediation
	7 Moderation
		7.1 Moderating Role of Public-Private Partnership Among Point of Service and Work Place Learning
		7.2 Moderating Role of Public-Private Partnership Among Work Place Learning and Creativity
	8 Conclusion
	References
Prediction and Comparative Analysis of Few Most Impacted Countries by Coronavirus
	1 Introduction
		1.1 State of the Art
	2 Methodology
		2.1 Steps to Convert .xls to .arff
		2.2 The Specific Formula Used as Shown in Eq. (1)
		2.3 Weka Using Time Series Forecasting Package
	3 Evaluation Process
	4 Results and Analysis
	5 Conclusion
	References
An Efficient Method for Skin Cancer Detection Using Convolutional Neural Network
	1 Introduction
	2 Literature Review
	3 Methodology
		3.1 Classification with Light Weight CNN
	4 Experimental Study
	5 Conclusion
	References
Collective Behavior  in Community-Structured Network  and Epidemic Dynamics
	1 Introduction
		1.1 Motivation and Contribution
		1.2 Organization
	2 Related Works
	3 Methods
		3.1 Generation of Network with Community Structure
		3.2 Spreading Model
		3.3 Collective Behavior in a Community
	4 Experimental Design
	5 Results and Discussion
		5.1 Collective Behavior in Community and Epidemic Dynamics
		5.2 Initial Fear and Transmissibility of the Pathogen
		5.3 Role of Fear of Seed Node on Infection Propagation
		5.4 Impact of Varying Collective Behavior on Community-Wise Infection Spread
	6 Conclusion and Future Work
	References
Incorporating Semantics for Text Classification in Biomedical Domain
	1 Introduction
	2 Role of SVM and Multi-Label Learning
		2.1 Support Vector Machine (SVM)
	3 Dataset
	4 Proposed Model
	5 Feature Extraction and Representation
		5.1 Statistical Features
		5.2 Biomedical Features
		5.3 Linguistic Features
	6 Experiments and Results
	7 Conclusion
	References
COVID-19 Prediction from CT and X-Ray Scan Images: A Review
	1 Introduction
		1.1 COVID-19 Identification of Lung Infections with CT Imaging and Chest X-Ray (CXR)
		1.2 Artificial Intelligence in Medical Image Analysis
	2 Review Methodology
	3 Literature Review
		3.1 COVID-19 Identification of Lung Infection Using Deep Learning
		3.2 COVID-19 Identification of Lung Infection Using Machine Learning
		3.3 COVID-19 Identification of Lung Infection Using Ensemble Techniques
	4 Conclusion
	References
Design of a Prototypic Mental Health Ontology for Sentiment Analysis of Tweets
	1 Introduction
	2 Literature Survey
	3 Research Methodology for Ontology Creation
	4 Conclusion and Future Scope
	References
An Ensemble for Attendance Management with Face Visualization and Recognition Using Local Binary Pattern Histogram
	1 Introduction and Background
		1.1 Objectives and Scope
	2 Collation of Various Attendance Management Systems
		2.1 Near Field Communication
		2.2 Radio Frequency Identification
		2.3 Biometric Systems
	3 Proposed Model and Method
		3.1 Model Design
		3.2 Methodology
	4 Results
	5 Concerns and Scope
	References
Healthcare Question–Answering System: Trends and Perspectives
	1 Introduction
	2 A Review of QA Agents Used in Health Care
		2.1 Types of QA Agents
		2.2 Some Recent Healthcare QA Agents
	3 Neural Network-Based Healthcare QA Systems—A Discussion on the State of the Art
	4 Conclusions and Future Scope
	References
An Analysis of Word Sense Disambiguation (WSD)
	1 Introduction
	2 Description of the Task
		2.1 Choice of Word Senses
		2.2 Knowledge Resources from Outside the Organization
		2.3 Contextual Representation 
	3 Conclusion
	References
Classification of Breast Invasive Ductal Carcinomas Using Histopathological Images Based on Deep Learning Techniques
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 Convolutional Neural Networks
	4 Materials and Methods
		4.1 Description of the Dataset
		4.2 Annotate the Ground Truth
		4.3 Building Datasets Based on Image Patches
	5 Result and Discussion of the Experimental Work
	6 Conclusion
	References
Heart Disease Detection Using Machine Learning Techniques
	1 Introduction
	2 Literature Survey
	3 Algorithms Used
		3.1 Logistic Regression Methodology
		3.2 Decision Tree Methodology
		3.3 Random Forest Methodology
		3.4 Artificial Neural Network Methodology
	4 Dataset
		4.1 Feature Description
		4.2 Attributes’ Graph
		4.3 Architecture Diagram
	5 Data Preprocessing
	6 Accuracy
		6.1 Results and Discussion
	7 Conclusion and Future Work
	References
Evaluation of Spatiotemporal Fetal Cardiac Imaging Using Deep Learning Techniques
	1 Introduction
	2 Related Works
	3 Methodology
		3.1 Dataset Collection and Description
		3.2 Baseline Models
		3.3 Main Models
	4 Implementation
		4.1 Preprocessing
		4.2 Development of Models
	5 Results and Discussion
		5.1 Classification and Performance Evaluation of Five Standard View Fetal Heart
		5.2 Classification and Performance Evaluation of Normal Fetal Heart Versus Congenital Heart Disease (CHD) Lesions
	6 Conclusion
	References
Application of Deep Learning on Skin Cancer Prediction
	1 Introduction
	2 Literature Survey
	3 Dataset
	4 Data Preprocessing
	5 Proposed Methodology
		5.1 Data Augmentation
		5.2 Transfer Learning
		5.3 Efficient Net Model
		5.4 Implementation
		5.5 Stratified Shuffle Split
	6 Performance Evaluation Metrics
		6.1 Accuracy
		6.2 Precision
		6.3 Recall
		6.4 F1-Score
		6.5 Confusion Matrix
	7 Results and Discussion
	8 Conclusion
	References
Feature Analysis for Detection of Breast Cancer Thermograms Using Dimensionality Reduction Techniques
	1 Introduction
	2 Literature Survey
	3 Breast Cancer Methodology
		3.1 Dataset
		3.2 Proposed Approach
		3.3 Classification and Performance Parameters
	4 Experimental Result Discussion
	5 Conclusion
	References
Covid-19 Question-Answering System Based on Semantic Similarity
	1 Introduction
	2 Related Work
	3 Methodology
	4 Results
	5 Conclusion
	References
Impact of EEG Signals on Human Brain Before and After Meditation
	1 Introduction
	2 Connection Between Meditation and Stress
		2.1 Brain Wave
	3 EEG Analysis Process Before and After Meditation
	4 Comparative Analysis
	5 Proposed Methodology
	6 Conclusion
	References
COVID-19 Detection and Classification Method Based on Machine Learning and Image Processing
	1 Introduction
		1.1 Background
		1.2 Role of AI in Diagnosis of COVID-19
		1.3 COVID-19 Medical Image Processing
		1.4 COVID-19 Radiology Image Analysis Using Deep Learning
		1.5 Research Aim
	2 Literature Survey
		2.1 Research Gaps
	3 Proposed Work
	4 Conclusion
	References
Optimal Convolutional Neural Network Model for Early Detection of Lung Cancer on CT Images
	1 Introduction and Background
		1.1 Literature Survey
	2 Proposed Model and Method
		2.1 Model Development Using CNN
		2.2 Methodology
	3 Results
	4 Scope
	References
Lung Cancer Diagnosis Using Deep Convolutional Neural Network
	1 Introduction
	2 Literature Review
	3 Methods
		3.1 Data Collection
		3.2 Pre-processing
		3.3 Image Data Augmentation
		3.4 Convolutional Neural Network (CNN)
		3.5 Flask App
	4 Results
		4.1 To Improve the Quality of CT Scans Images Depicting Different Types of Lung Cancer
		4.2 To Classify the Lungs of a Person that is Infected with a Type of Lung Cancer and Severity Using a Two-Dimensional Convolution Neural Network (CNN)
	5 Discussion
	6 Conclusion
	References
A Comprehensive Review of Brain Tumor Detection and Segmentation Techniques
	1 Introduction
	2 Deep Learning Approaches for Brain Tumour Detection
	3 Radiomic Analysis for Brain Tumour Detection
	4 Segmentation Approaches for Brain Tumour Detection
	5 Datasets
	6 Open Challenges and Research Directions
	7 Concluding Remarks
	References
Early Depression Detection Using Textual Cues from Social Data:  A Research Agenda
	1 Introduction
	2 Technical Background
		2.1 Dataset
		2.2 Feature Engineering
		2.3 Feature Encoding
		2.4 Approaches
	3 Related Work
	4 Preparing Data
		4.1 Building Dataset
		4.2 Preprocessing
		4.3 Lexicon Building
	5 Examining the Data Needs of Various ML and DL Methods
		5.1 Benchmark Model Summary
		5.2 Role of Number of Users in Classification Accuracy
		5.3 Role of Number of Posts per User in Classification Accuracy
	6 Research Agenda
	7 Conclusion
	References