The last few years have seen a growing momentum in the Biomedical and Bioinformatics areas. As an example let us just think of the considerable attention that Linked Data gained as a mechanism to enable the provision and sharing of data in Life Sciences. This trend has resulted in the generation of a vast amount of information and data that can be more efficiently exploited if categorized and cataloged (possibly according to different dimensions) therefore creating added value. Knowledge Management technologies enable more semantics to be represented, exchanged, and inferred thus supporting greater interoperability between systems and by explicitly identifying links between independently created knowledge-based systems. Cutting-edge research into web science, medical ontologies and recommender systems provide further opportunities for development of personalized intelligent systems for public and global health.

The knowledge management community has demonstrated to be active on digital health related topic. In the last year several contributions have been provided in the main Knowledge Management and Semantic Web conferences and journals. Similarly, there has been considerable interest in knowledge management related topics (ontologies, stream reasoning, linked data) in the main health informatics, digital health and life sciences conferences. Prestigious conferences and journals including SWAT4LS, Digital Health, AI in Medicine, AIME include topic of interests such as AI-based clinical decision making, Medical knowledge engineering, Automated reasoning and meta-reasoning in medicine.

As a result of this maturing area many large IT vendors such as IBM, Google and Microsoft have well established applications of knowledge management technologies in the area of healthcare (e.g. IBM’s Watson Oncology) that they supply to national health service providers such as the British NHS. Similarly, a growing number of start ups are using ontologies, knowledge graph and semantic based reasoning to recommend treatments, model electronic health records and automate the scheduling of patients.

The workshop on Knowledge Management Technologies for Healthcare aims cover a wide spectrum of topics concerned with the integration of knowledge management technologies within the healthcare domain including, communities of practice and social networks, analytics and engagement with tracking and monitoring wearable devices, big data, public health surveillance, persuasive technologies, epidemic intelligence, participatory surveillance, and emergency medicine.


Topics of interest

Topics include but are not limited to:

  • Big data and big ontology in Healthcare
  • Biomedical ontology mapping
  • Clinical trial generalizability assessment using ontologies
  • Computer-interpretable clinical guidelines
  • Computer-interpretable clinical trial eligibility criteria
  • Data mining or machine learning on biomedical, clinical or social web data
  • Decision support systems in medicine
  • Development of semantic applications for medicine and healthcare
  • Health knowledge management
  • Robotic systems for assisted living
  • Information Extraction on biomedical, clinical, or social web data
  • Medical knowledge graphs
  • Ontology development, enrichment and alignment in healthcare and life sciences
  • Ontology-based text mining and natural language processing
  • Ontology-based analysis on biomedical, clinical, or social web data
  • Quality assurance of ontologies and controlled terminologies
  • Rule-based formalizations for Healthcare systems
  • Reasoning and processing of medical knowledge
  • Semantic annotation of medical images and documents
  • Semantic annotation on biomedical, clinical or social web data
  • Semantic interoperability for clinical trial data
  • Semantic interoperability for Electronic Health Records (EHRs)
  • Semantic research for biomedical science
  • Semantic technology for telemedicine
  • Semantically-enabled systems in medicine and healthcare
  • Serious games for healthcare integrating semantic solutions
  • Temporal/spatial reasoning and data processing in Healthcare