
Health Information Science
11th International Conference, HIS 2022, Virtual Event, October 28-30, 2022, Proceedings
Springer (Publisher)
Published on 26. October 2022
Book
Paperback/Softback
XII, 326 pages
978-3-031-20626-9 (ISBN)
Description
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.
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.
More details
Series
Edition
1st ed. 2022
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
24 s/w Abbildungen, 75 farbige Abbildungen
XII, 326 p. 99 illus., 75 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 19 mm
Weight
517 gr
ISBN-13
978-3-031-20626-9 (9783031206269)
DOI
10.1007/978-3-031-20627-6
Schweitzer Classification
Other editions
Additional editions

Agma Traina | Hua Wang | Yong Zhang
Health Information Science
11th International Conference, HIS 2022, Virtual Event, October 28-30, 2022, Proceedings
E-Book
10/2022
Springer
€80.24
Available for download
Content
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.