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Health Information Science: 13th International Conference, HIS 2024, Hong Kong, China, December 810, 2024, Proceedings [Pehme köide]

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  • Formaat: Paperback / softback, 340 pages, kõrgus x laius: 235x155 mm, 75 Illustrations, color; 20 Illustrations, black and white; XIII, 340 p. 95 illus., 75 illus. in color., 1 Paperback / softback
  • Sari: Lecture Notes in Computer Science 15336
  • Ilmumisaeg: 16-May-2025
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 981965596X
  • ISBN-13: 9789819655960
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Health Information Science: 13th International Conference, HIS 2024, Hong Kong, China, December 810, 2024, ProceedingsSuurem pilt
  • Formaat: Paperback / softback, 340 pages, kõrgus x laius: 235x155 mm, 75 Illustrations, color; 20 Illustrations, black and white; XIII, 340 p. 95 illus., 75 illus. in color., 1 Paperback / softback
  • Sari: Lecture Notes in Computer Science 15336
  • Ilmumisaeg: 16-May-2025
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 981965596X
  • ISBN-13: 9789819655960
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9789819655960.html
Märksõnad:
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.NetA 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.