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Transforming Healthcare with Knowledge Graphs and AI: Integration, Analysis, and Visualization

Session Track: Data Science

Session Time:

Session description

In this presentation, Amna will cover multifaceted applications of knowledge graphs within the domain of data science and AI-driven healthcare. We will explore advanced techniques for integrating diverse data sources into comprehensive knowledge graphs, employing graph-based machine learning, and enhancing data visualization. Attendees will gain insights into the methodologies for constructing robust knowledge graphs; optimizing them for AI applications; and leveraging them for advanced semantic cohort searches, disease trajectory analysis, personalized treatment recommendations, and advanced data visualizations. The talk will also highlight practical challenges and best practices, showcasing real-world use cases that demonstrate the transformative potential of knowledge graphs in improving clinical decision-making and personalized patient care.

Speaker

photo of Amna Basharat

Amna Basharat

Assistant Professor, FAST National University of Computer & Emerging Sciences

Dr. Amna Basharat is currently serving as an Assistant Professor at the Department of Computer Science, at the National University of Computer and Emerging Sciences, Islamabad, Pakistan. She completed her PhD (Computer Science) in Dec 2016, under the prestigious Fulbright Scholarship Program, from the University of Georgia, USA. She is currently heading the IKNEX (Knowledge, Intelligence and Experience) Research lab where her research spans across ontology & knowledge graph engineering, linked data and user experience. She is currently actively involved in designing ontologies in the area of digital humanities, cultural heritage and healthcare. She is currently a Research Fellow and a Princial AI Research Engineer with CureMD Healthcare.