Health Information Science
Springer Nature Switzerland AG (Verlag)
978-981-96-5596-0 (ISBN)
This book LNCS 15336 constitutes the refereed proceedings of the 13th International Conference on Health Information Science, HIS 2024, held in Hong Kong, China, during December 8-10, 2024.
The 18 full papers and 11 short papers were carefully reviewed and selected from 59 submissions. The scope of the conference includes:
(1) medical/health/biomedicine information resources, such as patient medical records, devices and equipments, software and tools to capture, store, retrieve, process, analyze, and optimize the use of information in the health domain;
(2) data management, data mining, and knowledge discovery, all of which play a key role in decision-making, management of public health, examination of standards, privacy and security issues;
(3) computer visualization and artificial intelligence for computer-aided diagnosis;
(4) development of new architectures and applications for health information systems.
Artificial Intelligence in Enhancing Electronic Health Record Systems: A Comprehensive Survey.- Complex Query Optimization in Sepsis Data Using Learned Index with Data Transformation.- A Novel Feature Selection Framework Based on Large Language Models.- LTGAN: Multi-label Time-series GAN with Constraints for Electronic Health Records Generation.- Multi-condition Join Query Optimization For Disease-specific Data Exploration Based On Data Lake.- Multi-modal Medical Data Management Platform Based on Data Lake.- Comparative Study of Machine Learning Algorithms for IoT Cyber Threat Detection in Healthcare Information Systems.- Myocardial Band Transformer Network for Detecting Myocardial Ischemia in 2D Echocardiography.- Deep Learning-Enabled Electronic Health Records for Accurate Diagnosis of Cardiovascular Diseases: A Retrospective, Prospective, Diagnostic Study.- V-GnNet: Voxel and Graph Node Based Network for Continuously Consistent Artery and Vein Classification in Non-contrast CT Images.- Multilabel Classification for Cancer Subtypes.- TG.Net A deep learning model combining attention mechanism for effective prediction of multi stages of Chronic Kidney Disease.- A Deep Transfer Learning Approach for Predicting Diabetes Complications Using Genomic Data.- Using machine learning to predict the risk severity of late effects of a childhood rhabdomyosarcoma survivors.- Predicting C-section Outcomes among Bangladeshi Women: A Comparative Study of Machine Learning Techniques.- Exploring Relations between Depression and Cognitive Impairment.- Investigating Roles of Immune Functions in Depression by Using Knowledge Graph Approach.- EEG Sleep Classification Based on Fourier-Bessel Technique Coupled with LS-SVM.- An AI driven framework for EEG based-BCI technology.- Perceptions of Academic Performance and Mental Health Among Pharmacy Students Across Different Learning Modalities.- Epilepsy Detection from Weighted EEG Graph (WEG) using Novel Feature- Normalized Weighted Forgotten Topological Index (NWFT-index).- Extended Knowledge Graphs of Depression.- IBDR-Net: A Computerized Framework for Irregular Brain Signal Data Recognition.- Physical Human Activity Recognition Based on Spectral Graph Wavelet Transforms Integrated with Machine Learning Model.- Robust Approach for Human Activity Recognition Using Decomposition Technique Based Machine Learning Models.- The Impact of COVID-19 and the Ukrainian war on the share market index for the Australian Financial sector.- The Impact of COVID-19 on Global GMAT Test-Taking Patterns: A Statistical Analysis.- A Geriatric Disease Medical Consultation System Based on Multi-Agent Architecture and Knowledge Graph.- Impact of social media on heart health-related behaviours in health promotion interventions: sentiment analysis of tweets linked to the American Heart Month campaigns.
| Erscheinungsdatum | 20.05.2025 |
|---|---|
| Reihe/Serie | Lecture Notes in Computer Science |
| Zusatzinfo | 75 Illustrations, color; 20 Illustrations, black and white |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Medizin / Pharmazie | |
| Technik ► Maschinenbau | |
| Technik ► Medizintechnik | |
| Schlagworte | Applied Computing • applied informatics • Bioinformatics • Computer Aided Diagnosis • Data Mining • health care information systems • Health Informatics • health information • Health Science • Knowledge Discovery • life and medical science |
| ISBN-10 | 981-96-5596-X / 981965596X |
| ISBN-13 | 978-981-96-5596-0 / 9789819655960 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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