KDH-2017: KDH 2017 - Knowledge Discovery from Healthcare Data (KDH) Workshop Melbourne, Australia, August 19-26, 2017 |
Conference website | https://sites.google.com/site/kdhijcai2017/ |
Submission link | https://easychair.org/conferences/?conf=kdh2017 |
Abstract registration deadline | May 1, 2017 |
Submission deadline | May 12, 2017 |
The Knowledge Discovery from Healthcare Data (KDH) workshop series was established in 2016 to foster discussion and present research efforts that leverage the large amounts of clinical, biological and physiological data to expedite knowledge discovery in healthcare. Following a successful 2016 KHD workshop and aligning with this year’s IJCAI theme of autonomy, the 2017 KDH workshop will support areas of research covered by the novel concept of learning healthcare systems.
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:
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Long papers (6 pages + 1 page references): Long papers should present original research work and be no longer than seven pages in total: six pages for the main text of the paper (including all figures but excluding references), and one additional page for references.
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Short papers (3 pages + 1 page references): Short papers may report on works in progress, descriptions of available datasets, as well as data collection efforts. Position papers regarding potential research challenges are also welcomed. Short paper submissions should be no longer than four pages in total: three pages for the main text of the paper (including all figures but excluding references), and one additional page for references.
Both long and short papers must be formatted according to IJCAI guidelines and submitted electronically through easychair.
List of Topics
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Machine Learning, Knowledge Discovery and Data Mining
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Biomedical Knowledge Acquisition and Knowledge Management
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Visual Analytics in Biomedicine
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Artificial neural network models or deep learning approaches for healthcare data analytics
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Bayesian Networks and Reasoning Under Uncertainty
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Predictive and prescriptive analyses of healthcare data
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Probabilistic analysis in medicine
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Development of novel diagnostic and prognostic tests utilising quantitative data analysis
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Integration and application of Biomedical Ontologies and Terminologies
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Knowledge graph construction from biomedical data and resources
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Knowledge-driven approaches for information retrieval and data mining
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Ontology based data/system integration in biomedical domain
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AI methods that combine logical reasoning and machine learning technologies
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Autonomous and Multi-agent Systems
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AI methods in Telemedicine and eHealth
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Mobile agents in hospital environment
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Applications of AI solutions for Ambient Assisted Living
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Medical Decision Support Systems, including Recommender Systems
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Patient monitoring and diagnosis through autonomous processes
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Automation of clinical trials, including implementation of adaptive and platform trial designs.
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Applications of wearables in healthcare
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Patient Empowerment through Personalised patient-centred systems
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Autonomous and remote care delivery.
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Patient Engagement Support (Personal Health Record)
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Natural Language Processing
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Novel biomedical document classification and information retrieval technologies
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Semantic annotations and applications on Electronic Health Records, case reports, literature or relevant text resources
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Knowledge abstraction, classification, and summarisation from literature or electronic health records
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Biomedical Imaging and Signal Processing
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Behaviour Medicine
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Computerised Clinical Practice Guidelines and Protocols
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Healthcare Process and Workflow Management
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Solutions to the basic methodological and technological problems associated to the real deployment of healthcare systems: security, privacy, stakeholder acceptance, ethical issues, etc.
Further Information
For detailed information on the workshop, please visit https://sites.google.com/site/kdhijcai2017/.