Semantic Web Technologies for Health Data Management
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Algorithms for Multidisciplinary Applications".
Deadline for manuscript submissions: closed (24 April 2022) | Viewed by 559
Special Issue Editors
Interests: big data management; personalization; recommender systems; entity resolution; data exploration; data analytics; responsible data management
Special Issues, Collections and Topics in MDPI journals
Interests: big data management; semantic interoperability; data series; information integration; AI
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recent advancements in healthcare have brought to the foreground the need for flexible access to health-related information and created an ever-growing demand for efficient data management infrastructures. To this direction, many challenges must first be overcome, enabling seamless, effective, and efficient access to several health data sets and novel methods for exploiting the existing information. This Special Issue aims at putting together research in the fields of semantic web, data management, and health informatics to discuss the challenges in healthcare data management and to propose new solutions for the next generation data-driven healthcare systems.
Dr. Kostas Stefanidis
Dr. Haridimos Kondylakis
Guest Editors
Manuscript Submission Information
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Keywords
- Artificial intelligence (AI) and machine learning in health data management
- Ontologies and data models on the health domain
- Semantic integration of heterogeneous health data sources
- Wearable and sensor data integration with health data
- Web-scale and cloud-based health data management systems
- NoSQL and graph databases for health data management
- Semantic search and reasoning over health data
- Recommendations for health data
- Exploratory search of health data via query reformulation, autocompletion, type-ahead search, and approximate query answering
- Health data exploration through visualization
- Analytics over large-scale health data
- Personal health apps
- Data quality, profiling, and uncertainty of health data
- Data provenance and trust of health data
- Data versioning, evolution, change detection and representation
- Generation and aggregation of health semantics
- Natural language processing and text mining techniques for health data
- Novel techniques for security, privacy, and sharing of health data
- Knowledge graph construction on health data
- Blockchain-based solutions for health data management
- Innovative use of semantic technologies for health data
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