Presentations
Invited Talk
Machine Learning in Health: Opportunities and Challenges
Text Classification and Summarization
ROLE AND APPLICATIONS OF PRE-TRAINED LANGUAGE MODELS and DEEP LEARNING TECHNIQUES IN THE BIOMEDICAL DOMAIN
Tutorial Presentation
Decision Support Systems in the Era of Evidence-Based and Precision Medicine
HEALTHINF 2018, 11th International Conference on Health Informatics, January 19-21, 2018, FUNCHAL, Madeira, Portugal.
Decision support systems and services have long been utilized to assist clinicians and physicians in making affective decisions while reducing the chance of medical errors and increasing healthcare quality and efficiency. Many different kinds of decision support systems (DSSs) and approaches are in action for their potential to improve the overall healthcare decision process. In the existence of Evidence-based medicine and with the advent of precision medicine, more informed healthcare is envisioned to be practiced. The contemporary DSSs need to be channelized to incorporate the very need of precision medicine components such as genomic and environmental data in addition to patient demographics and clinical data.
In this tutorial session we will elaborate to talk about DSSs, advancements in DSSs, evidence-based medicine, evidence-adaptive DSSs, precision medicine, and role of DSSs in precision medicine. A set of technologies will be discussed while speaking the above-mentioned topics such as; model-driven (e.g. rule-based, case-based), data-driven (e.g. machine learning, deep learning), natural language preprocessing, information retrieval, information extraction, and others.
This tutorial will provide a fair learning opportunity to the audience in terms of understanding the changing role of popular techniques in the domains of health and wellness. They will be able to connect the dots of different co-existed technologies while they are researching, developing, or implementing enterprise level systems and services.
Detailed Outline
Overview of health informatics concepts
Introduction to decision support systems (DSS)
Components of DSS
Types of DSS
Knowledge Bases and Standardization
Knowledge Acquisition Methods
Model-driven (expert-driven) vs data- driven(machine-driven) approaches
Evidence-based Medicine and Evidence-Adaptive DSS
Overview of Evidence-based Medicine (EBM)
Key elements of EBM
Challenges in EBM process
Role of automation in EBM
Integration of DSS with EBM
Concept and Development Strategies of Evidence-Adaptive CDS
Precision Medicine and Precise Recommendation
Briefs of Precision Medicine Initiative
Components of Precision Medicine (PM)
Role of DSSs in the Era of PM
Research and Implementation challenges
Conclusion
Putting together all the three major topics: DSS, EBM, and PM
Conclusion and Future Roadmap