The AI-Driven Future of Health Data Science
Chronic and polymedicated patients represent a critical healthcare priority, driving substantial costs and posing significant safety risks. As the population ages, the prevalence of patients receiving multiple concurrent medications (and the potential for adverse interactions) continues to escalate. In this seminar we will discuss how comprehensive patient-level datasets, encompassing demographics, clinical events, diagnoses, and prescription histories, can be leveraged through both expert-guided methodologies and advanced data-driven approaches to identify potentially harmful drug interactions. By applying sophisticated patient clustering techniques based on biomedical criteria, we explore how medical ontologies can effectively structure and interrelate complex clinical and pharmacological data. Furthermore, we highlight the transformative potential of artificial intelligence in health research, particularly its ability to analyze intricate data structures to uncover previously hidden clinical patterns. These capabilities enable more precise diagnostic insights and support the development of safer, truly personalized treatment strategies.
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- Carleton University
- 1125 Colonel By Drive
- Ottawa, Ontario
- Canada K1S5B6
- Building: Mckenzie building
- Room Number: ME4463
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- Co-sponsored by CU@EMBS
Speakers
Dr. Rocío Romero Zaliz
The AI-Driven Future of Health Data Science
Biography:
Dr. Rocío Romero Zaliz is Associate Professor at the University of Granada, Spain, specializing in computational biology, data science, and computational intelligence. She is affiliated with the Data Science and Computational Intelligence Research Institute (DaSCI) at the University of Granada and serves as the Assistant Director of Research, Transfer, and Teaching at the Centre for Research in Information and Communication Technologies (CITIC-UGR). Her research interests include artificial intelligence applications in medicine and health, as well as the development of metaheuristics and data science methodologies. She authored a book titled "Con-ciencia de datos," about data science which makes complex concepts accessible to a broad audience.