KDH-2019: The 4th International Workshop on Knowledge Discovery in Healthcare Data

Country: China

City: Macao

Abstr. due: 10.05.2019

Dates: 10.08.19 — 12.08.19

Area Of Sciences: Physics and math; Medicine;

Organizing comittee e-mail: n.wiratunga@rgu.ac.uk

Organizers: IJCAI Committee


In this workshop we wish to address the challenge of leveraging knowledge-based models that can utilise patient-focused data to improve care delivery to bring about "learning healthcare systems". The notion of the learning healthcare system encompasses research in prominent areas of Artificial Intelligence including language engineering, data mining, knowledge representation & reasoning, learning and autonomous systems.

This workshop is part of the IJCAI-workshop series and will build on previously held successful Knowledge Discovery in Healthcare Data workshops by welcoming contributions providing insight on the extent to which AI techniques have successfully penetrated the healthcare field, interaction among AI techniques to achieve a successful learning healthcare system and the distinction between AI and non-AI models needed in modern healthcare environments. The workshop will focus on discussing issues in data extraction and assembly, knowledge discovery and personalised decision support to care providers and self-care aiding tools to patients.
List of Topics

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

    Theme-related contributions:
        Analysis of the rise of techniques and approaches, and the decline of techniques and approaches for knowledge discovery in healthcare
        Analyses of the interaction between AI subfields serving the learning healthcare system
        AI and non-AI techniques to solve the basic methodological and technological problems associated to the real deployment of health-care agent-based systems: security, privacy, stakeholder acceptance, ethical issues, etc.
    Data extraction, organisation & assembly:
        Knowledge-driven and data-driven approaches for information retrieval and data mining
        Multilevel data integration in healthcare, e.g. behavioural data, diagnoses, vitals, radiology imaging, Doctor's notes, phenotype, and different omics data, including multi-agent approaches.
        Integration and use of medical ontologies.
        Knowledge abstraction, classification, and summarization from literature or electronic health records
    Knowledge discovery & analytics
        Handling uncertainty in large healthcare datasets: dealing with missing values and non-uniformly sampled data
        Detecting and extracting hidden information from healthcare data
        The rise of Artificial neural network models or deep learning approaches for healthcare data analytics
        Extracting causal relationships from healthcare data
        Predictive and prescriptive analyses of healthcare data
        Applications of probabilistic analysis in medicine
        Development of novel diagnostic and prognostic tests utilising quantitative data analysis
    Personalisation and decision support
        Mobile agents in hospital environment
        Patient Empowerment through Personalised patient-centred systems
        Autonomous and remote care delivery.
        Medical Decision Support Systems, including Recommender Systems
        Automation of clinical trials, including implementation of adaptive and platform trial designs.
        Applications of IoT (wearables, sensors, etc.)  in healthcare
    Provenance, Security and privacy of health data
        Frameworks for data security management
        Transparency and explainability
        Provenance of health data
    Multi-modal Low-back Pain Exercise Recognition challenge
        Scientific papers reviewing existing machine learning models or presenting novel machine learning models for reasoning with multi-modal sensor data
        Papers that addresses the workshop challenge in areas such as representation, translation, alignment, fusion and co-learning.


Conference Web-Site: https://sites.google.com/view/kdh2019