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KDH@IJCAI 2017 : The 2nd International Workshop on Knowledge Discovery in Healthcare Data (KDH) - aligning with IJCAI 2017

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Link: https://sites.google.com/site/kdhijcai2017/
 
When Aug 19, 2017 - Aug 19, 2017
Where Melbourne, Australia
Submission Deadline May 5, 2017
Notification Due Jun 5, 2017
Final Version Due Jul 5, 2017
Categories    artificial intelligence   computer science   machine learning   health care
 

Call For Papers

****New*****: Due to many requests, the deadline has been extended to Friday the 12th of May.

****New*****: selected papers will be invited to submit extended versions to the Journal of Health Informatics Research (http://www.springer.com/computer/information+systems+and+applications/journal/41666), published by Springer

The notion of the learning healthcare system has been put forward to denote the translation of routinely collected data into knowledge that drives the continual improvement of medical care by seamlessly embedding learned best practices in the healthcare delivery process. This notion has been described in many forms, but each follows a similar cycle of assembling, analyzing and interpreting data from multiple sources (clinical records, guidelines, patient-provided data including wearables, omic data, etc..), followed by feeding the acquired knowledge back into clinical practice. This framework aims to provide personalised recommendations and decision support tools to aid both patients and care providers, to improve outcomes and personalise care.


Contributions are welcome in areas including, but not limited to, the following:

* Machine Learning, Knowledge Discovery and Data Mining
-- Biomedical Knowledge Acquisition and Knowledge Management
-- Visual Analytics in Biomedicine
-- Artificial neural network models or deep learning approaches for healthcare data analytics
-- Bayesian Networks and Reasoning Under Uncertainty
-- Predictive and prescriptive analyses of healthcare data
-- Probabilistic analysis in medicine
-- Development of novel diagnostic and prognostic tests utilising quantitative data analysis

* Integration and application of Biomedical Ontologies and Terminologies
-- Knowledge graph construction from biomedical data and resources
-- Knowledge-driven approaches for information retrieval and data mining
-- Ontology based data/system integration in biomedical domain
-- AI methods that combine logical reasoning and machine learning technologies

* Autonomous and Multi-agent Systems
-- AI methods in Telemedicine and eHealth
-- Mobile agents in hospital environment
-- Applications of AI solutions for Ambient Assisted Living
-- Medical Decision Support Systems, including Recommender Systems
-- Patient monitoring and diagnosis through autonomous processes
-- Automation of clinical trials, including implementation of adaptive and platform trial designs.
-- Applications of wearables in healthcare
-- Patient Empowerment through Personalised patient-centred systems
-- Autonomous and remote care delivery.
-- Patient Engagement Support (Personal Health Record)

* Natural Language Processing
-- Novel biomedical document classification and information retrieval technologies
-- Semantic annotations and applications on Electronic Health Records, case reports, literature or relevant text resources
-- Knowledge abstraction, classification, and summarisation from literature or electronic health records

* Biomedical Imaging and Signal Processing
* Behaviour Medicine
* Computerised Clinical Practice Guidelines and Protocols
* Healthcare Process and Workflow Management
* Solutions to the basic methodological and technological problems associated to the real deployment of healthcare systems: security, privacy, stakeholder acceptance, ethical issues, etc.

Submissions

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.

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: https://easychair.org/conferences/?conf=kdh2017.

The papers accepted for KDH 2017 will be published in the international proceedings volume. This proceedings volume will be published electronically and indexed by Google Scholar and DBLP.


Organising Committee

Zina Ibrahim, King's College London (zina.ibrahim@kcl.ac.uk)
Honghan Wu, King's College London (honghan.wu@kcl.ac.uk)
Richard Dobson, University College London (r.dobson@ucl.ac.uk)
Spiros Denaxas, University College London (s.denaxas@ucl.ac.uk)
Kerstin Bach, Norwegian University in Science and Technology (kerstin@idi.ntnu.no)
Nirmalie Wiratunga, Robert Gordon University (n.wiratunga@rgu.ac.uk)
Stewart Massie, Robert Gordon University (s.massie@rgu.ac.uk)
Sadiq Sani, Robert Gordon University (s.sani@rgu.ac.uk)

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