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 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.
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Inhaltsangabe
Applications of Health and Medical Data.- Evidence extraction to validate medical claims in fake news detection.- Detection of obsessive-compulsive disorder in Australian children and adolescents using machine learning methods.- An Anomaly Detection Framework Based on Data Lake for Medical Multivariate Time Series.- Anomaly Detection on Health Data.- DRAM-Net: A Deep Residual Alzheimer's Diseases and Mild Cognitive Impairment Detection Network Using EEG Data.- An Intelligence Model for Blood Pressure Estimation from Photoplethysmography Signal.- Tailored Nutrition Service to Reduce the Risk of Chronic Diseases.- Combining Process Mining And Time Series Forecasting To Predict Hospital Bed Occupancy.- HGCL: Heterogeneous Graph Contrastive Learning for Traditional Chinese Medicine Prescription Generation.- Fractional Fourier Transform Aided Computerized Framework for Alcoholism Identification in EEG.- Learning optimal treatment strategies for sepsis usingonline reinforcement learning in continuous space.- Health and Medical Data Processing.- MHDML:Construction of A Medical Lakehouse for Multi-source Heterogeneous Data.- Data Exploration Optimization for Medical Big Data.- Improving Data Analytic Performance in Health Information System with Big Data Technology.- HoloCleanX: A Multi-source Heterogeneous Data Cleaning Solution Based on Lakehouse Platform.- The construction and validation of an automatic crisis balance analysis model.- Assessing the Utilization of TELedentistry from perspectives of earlycareer dental practitioners - development of the UTEL Questionnaire.- Genetic Algorithm for Patient Assignment Optimization in Cloud Healthcare System.- Research on the Crisis Intervention Strategy Service System.- Towards a Perspective to Analyze Emergent Sytems in the Health Domain.- Health and Medical Data Mining via Graph-based Approaches.- Food recommendation for mental health by using knowledge graph approach.- Medical Knowledge Graph Construction Based on Traceable Conversion.- Medical Knowledge Graph Construction Based on Traceable Conversion.- Alcoholic EEG Data Classification Using Weighted Graph Based Technique.- Health and Medical Data Classification.- Optical Coherence Tomography Classification based on Transfer Learning and RA-Attention.- Intelligent Interpretation and Classification of Multivariate Medical time series based on Convolutional Neural Networks.- ECG Signals Classification Model Based on Frequency domain Features Coupled with Least Square Support Vector Machine (LS-SVM).- Cluster analysis of low-dimensional medical concept representations from Electronic Health Records.
Applications of Health and Medical Data.- Evidence extraction to validate medical claims in fake news detection.- Detection of obsessive-compulsive disorder in Australian children and adolescents using machine learning methods.- An Anomaly Detection Framework Based on Data Lake for Medical Multivariate Time Series.- Anomaly Detection on Health Data.- DRAM-Net: A Deep Residual Alzheimer's Diseases and Mild Cognitive Impairment Detection Network Using EEG Data.- An Intelligence Model for Blood Pressure Estimation from Photoplethysmography Signal.- Tailored Nutrition Service to Reduce the Risk of Chronic Diseases.- Combining Process Mining And Time Series Forecasting To Predict Hospital Bed Occupancy.- HGCL: Heterogeneous Graph Contrastive Learning for Traditional Chinese Medicine Prescription Generation.- Fractional Fourier Transform Aided Computerized Framework for Alcoholism Identification in EEG.- Learning optimal treatment strategies for sepsis usingonline reinforcement learning in continuous space.- Health and Medical Data Processing.- MHDML:Construction of A Medical Lakehouse for Multi-source Heterogeneous Data.- Data Exploration Optimization for Medical Big Data.- Improving Data Analytic Performance in Health Information System with Big Data Technology.- HoloCleanX: A Multi-source Heterogeneous Data Cleaning Solution Based on Lakehouse Platform.- The construction and validation of an automatic crisis balance analysis model.- Assessing the Utilization of TELedentistry from perspectives of earlycareer dental practitioners - development of the UTEL Questionnaire.- Genetic Algorithm for Patient Assignment Optimization in Cloud Healthcare System.- Research on the Crisis Intervention Strategy Service System.- Towards a Perspective to Analyze Emergent Sytems in the Health Domain.- Health and Medical Data Mining via Graph-based Approaches.- Food recommendation for mental health by using knowledge graph approach.- Medical Knowledge Graph Construction Based on Traceable Conversion.- Medical Knowledge Graph Construction Based on Traceable Conversion.- Alcoholic EEG Data Classification Using Weighted Graph Based Technique.- Health and Medical Data Classification.- Optical Coherence Tomography Classification based on Transfer Learning and RA-Attention.- Intelligent Interpretation and Classification of Multivariate Medical time series based on Convolutional Neural Networks.- ECG Signals Classification Model Based on Frequency domain Features Coupled with Least Square Support Vector Machine (LS-SVM).- Cluster analysis of low-dimensional medical concept representations from Electronic Health Records.
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