Navigating The Maze: Unveiling Rare Autoimmune Disorder with Help of Semantic Web Technologies, Ontology-based Knowledge Representation and Reasoning Driven by Panomic Data and Network Analysis
This keynote presents a ground-breaking approach to diagnosing complex illnesses and deciding on the best possible treatment, illustrated by a real-world case. The focus is on telling a story about integration of a vast arrays of patient medical records with peer-reviewed literature and interpretation of information combining the powers of knowledge representation and reasoning and advanced natural language processing, to analyse patient data spanning from the womb to the present.
The keynote will delve into the process that led to the discovery of an aggressive autoimmune disorder, highlighting the impact of this approach on the patient‚Äôs treatment and recovery. The presentation aims to propose the audience to use the presented methodologies in their practice, potentially leading to life-saving treatments. It’s an invaluable opportunity for healthcare professionals, researchers, and students to explore the intersection of AI, NLP, and healthcare, transforming the way complex medical conditions are understood and treated.
Dusan Milovanovic
Readiness Intelligence Consultant at World Health Organisation
Information and communication technologies leadership, including product management, systems engineering, business, application, data and technology architecture, computer and data science within the telecommunication industry as well as within life science, healthcare and public health.
Acted as a data architect and data scientist within the development of the Medical Informatics Platform in the scope of the Human Brain Project in a mission to connect patient biomedical data for timely discovery of biological signatures of rare diseases.
At the forefront of developing a public health knowledge representation and reasoning for connecting all-hazards One Health information for early-detection and verification of public health threats, rapid risk assessment and evidence-based decision making in public health emergencies with the World Health Organization, within the Epidemic Intelligence from Open Systems – a global public health intelligence community of practice.
