Health Information Science : 11th International Conference, HIS 2022, Virtual Event, October 28–30, 2022, Proceedings

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Preface Organization Contents Applications of Health and Medical Data Evidence Extraction to Validate Medical Claims in Fake News Detection 1 Introduction 2 Related Work 3 Proposed Method 3.1 Stage One (Selecting Similar Sentences) 3.2 Stage Two (Classifying Sentences) 4 Experiments Evaluation 4.1 Dataset Details 4.2 Experimental Settings 4.3 Results and Discussion 4.4 Supervised Case 4.5 Ablation Study 5 Conclusion References Detection of Obsessive-Compulsive Disorder in Australian Children and Adolescents Using Machine Learning Methods 1 Introduction 1.1 Contribution and Organization of the Paper 2 Proposed Methodology 2.1 Dataset 2.2 Data Processing 2.3 Methodology 3 Experimental Results and Discussion 4 Conclusion References An Anomaly Detection Framework Based on Data Lake for Medical Multivariate Time Series 1 Introduction 2 Related Work 3 Proposed Framework 4 Data Fusion and Exploration 5 Data Refinement 6 Anomaly Detection 6.1 Problem Statement 6.2 Convolutional LSTM Based Auto-encoder (CLBA) 6.3 Multi-scale Convolutional Recurrent Encoder-Decoder (MSCRED) 7 Case Study 8 Conclusion References Anomaly Detection on Health Data 1 Introduction 2 Key State-of-the-Art Methods 2.1 k Nearest Neighbors (kNN) 2.2 Local Outlier Factor (LOF) 2.3 Isolation Forest 2.4 Histogram Based Outlier Score 2.5 Sp 2.6 iNNE 2.7 SPAD 3 Experimental Evaluation 3.1 Datasets 3.2 Algorithm Implementation and Parameters 3.3 Evaluation Measures 4 Experimental Results and Discussion 5 Conclusion References DRAM-Net: A Deep Residual Alzheimer’s Diseases and Mild Cognitive Impairment Detection Network Using EEG Data 1 Introduction 2 Proposed DRAM-Net Framework 2.1 EEG Data Collection 2.2 Preprocessing 2.3 DRAM-Net Architecture to Identify AD, MCI, and HVs 3 Results and Discussions 4 Future Study and Conclusion References An Intelligence Approach for Blood Pressure Estimation from Photoplethysmography Signal 1 Introduction 2 Methodology and Material 2.1 Experimental Dataset 2.2 The Proposed Model 2.3 Machine Learning Approach to Estimate Blood Pressure 3 Experimental Results 3.1 Comparative Study with Different Feature Sets 4 Conclusions References Tailored Nutrition Service to Reduce the Risk of Chronic Diseases 1 Introduction 2 Chronic Diseases and Genes 3 Tailored Nutrition Intervention 3.1 Genetic Testing 3.2 Physical Examination 3.3 Health Condition and Lifestyle Evaluation 3.4 Tailored Nutrition 4 Conclusions References Combining Process Mining and Time Series Forecasting to Predict Hospital Bed Occupancy 1 Introduction 2 Theoretical Framework 3 Data 4 Methods 4.1 Process Mining of Patient Flows 4.2 Forecasting Algorithm 5 Experiments and Results 5.1 Modeling Hospital Patient Flows 5.2 Forecasting Bed Occupancy 5.3 Combining Patient Flows with A Forecasting Model 5.4 Model Extension with Knowledge 6 Discussion References HGCL: Heterogeneous Graph Contrastive Learning for Traditional Chinese Medicine Prescription Generation 1 Introduction 2 Related Work 2.1 TCM Prescription Generation 2.2 Graph Contrastive Learning 3 Preliminary 4 Our Proposed Model: HGCL 4.1 Data Augmentation on THIN 4.2 Node-level Contrastive Learning (NCL) 4.3 Semantic-Level Contrastive Learning (SCL) 4.4 Model Training 5 Experiments 5.1 Datasets 5.2 Baseline Methods 5.3 Herb Classification and Similarity Search 5.4 Prescription Generation 5.5 Ablation Study 5.6 Parameters Study 6 Conclusion References Fractional Fourier Transform Aided Computerized Framework for Alcoholism Identification in EEG 1 Introduction 2 Materials 3 Methods 3.1 Module 1: Pre-processing 3.2 Module 2: Fractional Fourier Transform as Feature Extraction 3.3 Module 3: Classification 4 Results and Discussions 5 Conclusion References Learning Optimal Treatment Strategies for Sepsis Using Offline Reinforcement Learning in Continuous Space 1 Introduction 2 Related Work 3 Preliminaries 3.1 Reinforcement Learning 3.2 Extrapolation Error 4 Datasets 5 Model Architecture 5.1 History Capture Model 5.2 Generative Model 5.3 Perturbation Model 5.4 Q-Networks 6 Experiment 6.1 Medical Action Selection 6.2 Reward Function 6.3 Training Process 7 Results 7.1 Result Analysis 7.2 Evaluation Metric 8 Conclusions References Health and Medical Data Processing MHDML: Construction of a Medical Lakehouse for Multi-source Heterogeneous Data 1 Introduction 2 Related Work 3 The Function Architecture of Medical Lakehouse 3.1 Data Ingestion Layer 3.2 Data Storage Layer 3.3 Data Management Layer 3.4 Data Scheduling Layer 3.5 Ecological Service Layer 3.6 Application Layer 4 Application and Implementation 5 Conclusion and Future Work References A Hybrid Medical Causal Inference Platform Based on Data Lake 1 Introduction 2 Related Work 3 Platform Design 3.1 Architecture and Workflow 3.2 Data-Driven vs Knowledge-Driven Methods 3.3 Integration of Data-Driven Expansion and Knowledge-Driven Simplification 4 Multi-source Heterogeneous Data Fusion 5 Exploratory Data Analysis 6 Causal Inference 7 Implementation and Use Case 8 Conclusion References Data Exploration Optimization for Medical Big Data 1 Introduction 2 Related Work 3 Data Storage and Migration 3.1 Data Migration Process 3.2 Implementation of Data Migration 4 Optimization Method for Medical Big Data 4.1 MIMIC-IV Data Exploration and Optimization Scheme 4.2 Importing Data into ORC Table and Creating Views 5 Experiment and Analysis 5.1 Experimental Environment 5.2 Experimental Data and Scheme 5.3 Experimental Results and Analysis 5.4 Analysis 6 Conclusion and Future Work References Improving Data Analytic Performance in Health Information System with Big Data Technology 1 Introduction 2 Related Works 3 Applying Big Data Technology to Improve Data Analytic Performance in Traditional Health Information Systems 3.1 Conceptual Model of Proposed Data Analytic Module for HIS 3.2 Implementation Model of HIS-BI 4 Experiment and Results 5 Conclusions and Future Work References HoloCleanX: A Multi-source Heterogeneous Data Cleaning Solution Based on Lakehouse 1 Introduction 2 Related Work 3 Architecture of HoloCleanX 4 Heterogeneous Data Fusion 5 Data Cleaning 5.1 Interactive Cleaning Procedure 5.2 Improved Inference Model 5.3 Data Restoration and Storage 6 System Implementation and Usage 6.1 Implementation 6.2 Usage 7 Conclusion and Future Work References The Construction and Validation of an Automatic Crisis Balance Analysis Model 1 Background 2 Method 2.1 Study Design 2.2 Enriching and Quantifing Aguilera’s Crisis Balance Theory 2.3 The Construction of Suicide Risk Assessment Model 2.4 The Construction of Cognitive Distortion and Interpersonal Relationship Analysis Model 2.5 Validation Methods 3 Results 3.1 Evaluation of Suicide Risk Assessment Model 3.2 Evaluation of Cognitive Distortion and Interpersonal Relationship Analysis Model 3.3 Validation of the Automatic Crisis Balance Analysis Model’s Predictive Efficacy 4 Discussion 5 Conclusion References Assessing the Utilisation of TELedentistry from Perspectives of Early Career Dental Practitioners - Development of the UTEL Questionnaire 1 Introduction 2 Aims 3 Methods 3.1 Ethics Approval 4 Results 4.1 Demographics 4.2 Diagnosis 4.3 Accessibility 4.4 Patient Care 4.5 Technology 4.6 Finances 5 Discussion 6 Conclusion References Genetic Algorithm for Patient Assignment Optimization in Cloud Healthcare System 1 Introduction 2 Related Work 3 Problem Definition 4 GA for PA 4.1 Representation 4.2 Crossover Operator 4.3 Mutation Operator 4.4 Overall Procedure 5 Experimental Setup 6 Experimental Result 6.1 Comparison with Existing Approaches 7 Conclusion References Research on the Construction of Psychological Crisis Intervention Strategy Service System 1 Introduction 2 Construction of Knowledge Graph 2.1 Data Sources 2.2 Structure Design of Knowledge Graph 2.3 Calculation of Sentence Vector 2.4 Storage of Knowledge Graph 3 Construction of Psychological Crisis Intervention System 3.1 Keyword Extraction Module 3.2 Knowledge Graph Retrieval Module 3.3 Generation of Intervention Text Module 3.4 Crisis Intervention Strategy Providing Module 3.5 System Performance Analysis 4 Conclusion References Towards a Perspective to Analyze Emergent Systems in Health Domain 1 Introduction 2 Background 3 Research Method 3.1 Define Research Terms 3.2 Inclusion, Exclusion, and Selection Criteria 4 Results 5 Consensus on Emergent Systems from the Literature 5.1 Perspective Do Analyze the Health Domain 5.2 Limitations 6 Conclusion and Future Research References Health and Medical Data Mining via Graph-based Approaches Food Recommendation for Mental Health by Using Knowledge Graph Approach 1 Introduction 2 Knowledge Enrichment 2.1 Data Source 2.2 Data Preprocessing 3 Knowledge Graph Construction 4 Cases Studies 4.1 The Properties of Food on Human Gut 4.2 The Effects of Food on Mental Disorder 5 Conclusion and Discussion 6 Future Work References Medical Knowledge Graph Construction Based on Traceable Conversion 1 Introduction 2 Related Work 3 Methodology 3.1 Conversion for Structured Data 3.2 Conversion for Unstructured Data 3.3 Conversion for Both Types of Data 4 Application 4.1 Applications for Structured Data 4.2 Applications for Unstructured Data 5 Conclusion References s Automated Knowledge Graph Construction for Healthcare Domain 1 Introduction 2 Related Work 3 A Framework for Knowledge Graph Development 4 Data Source for Knowledge Graph Learning 5 Knowledge Graph 5.1 Construction 5.2 Case Study 6 Future Work and Conclusions References Alcoholic EEG Data Classification Using Weighted Graph-Based Technique 1 Introduction 2 Methods 2.1 Mapping of EEG Data to Complex Network 2.2 Feature Extraction of Weighted Visibility Graph 2.3 Classification 3 Data and Experimental Results 4 Conclusion References Health and Medical Data Classification Optical Coherence Tomography Classification Based on Transfer Learning and RA-Attention 1 Introduction 2 TL-RA-EfficientNet Model 2.1 Data Preprocess 2.2 Transfer Learning Module 2.3 RA-EfficientNet 3 Results and Analysis 3.1 Experimental Settings 3.2 Performance Evaluation 3.3 Effect of Data Augmentation 3.4 Effect of Transfer Learning and Re-attention Modules 4 Conclusions References Intelligent Interpretation and Classification of Multivariate Medical Time Series Based on Convolutional Neural Networks 1 Introducion 2 Related Work 3 Methods 3.1 System Overview 3.2 Proposed H-RESNET Model 3.3 The Interpretability of the Proposed Classification Model 4 Experiment 4.1 Data Source 4.2 Pre-processing 4.3 Training Setting 4.4 Performance Metrics 4.5 Performance Metrics 4.6 Representation of Model Interpretability 5 Conclusion References ECG Signals Classification Model Based on Frequency Domain Features Coupled with Least Square Support Vector Machine (LS-SVM) 1 Introduction 2 Methodlogy and ECG Data 2.1 ECG Dataset 2.2 Proposed Model 2.3 ECG Segmentation 2.4 Optimization Triple Half Band Filter Bank (OTHFB) 2.5 Classification 2.6 Performance Evaluation Measurements 3 Experimental Results 3.1 Performance Evaluation Based on 10 Cross Validations 3.2 Classification Results Based on Different Kernel Functions 3.3 Performance Evaluation Based on Different Classification Models 3.4 Comparisons with Previous Studies 4 Conclusions References Cluster Analysis of Low-Dimensional Medical Concept Representations from Electronic Health Records 1 Introduction 2 Methodology 2.1 Data Pre-processing 2.2 Word2vec Embeddings 3 Results and Discussion 3.1 Medical Concept Prediction 3.2 Cluster Analysis of Medical Concepts 4 Conclusions References Author Index This book constitutes the refereed proceedings of the 11th International Conference on Health Information Science, HIS 2022, held in Virtual Event during October 28–30, 2022. The 20 full papers and 9 short papers included in this book were carefully reviewed andselected from 54 submissions. They were organized in topical sections as follows: ​applications of health and medical data; health and medical data processing; health and medical data mining via graph-based approaches; and health and medical data classification. This book constitutes the refereed proceedings of the 11th International Conference on Health Information Science, HIS 2022, held in Virtual Event during October 28-30, 2022. The 20 full papers and 9 short papers included in this book were carefully reviewed and selected from 54 submissions. They were organized in topical sections as follows: applications of health and medical data; health and medical data processing; health and medical data mining via graph-based approaches; and health and medical data classification