3 questions for...
Prof. Dr. Maria-Esther Vidal
Mentor
Prof. Maria-Esther Vidal brings to CAIMed her expertise in semantic data integration, symbolic reasoning, and knowledge graphs to develop cutting-edge explainable AI models. As the leader of the Scientific Data Management group, she specializes in semantic-driven approaches that combine symbolic reasoning and learning to uncover patterns that explain treatment effectiveness. Her goal is to create hybrid AI models by integrating semantic methods with neural learning. These hybrid AI models aim to identify patient conditions that predispose them to adverse treatment responses, thereby improving personalized healthcare interventions.
1.
How do you see the opportunities for development in your field of research through collaboration in CAIMed?
The collaboration at CAIMed will create the basis for the development of interpretable AI models tailored to the medical field. This collaboration provides the opportunity to explore new methods for understanding treatment effectiveness and side effects, leading to more personalized health interventions with tangible impact in practice. Collaboration with experimental groups has always been at the forefront of our research. We have always formulated the questions with the medical application in mind. In CAIMed, we have the opportunity to bring these many years of experience to the medical street.
2.
What potential and challenges do you see in interdisciplinary collaboration in CAIMed for your field?
The interdisciplinary collaboration within CAIMed offers the potential to utilize different expertise to develop innovative approaches that integrate computational methods into medical research. The challenges include harmonizing different terminologies and methods between disciplines, ensuring compliance with data protection and security regulations and dealing with the legal framework for medical research. framework for medical research.
3.
How important is collaboration between AI experts and healthcare professionals for the success of AI in medicine?
AI experts bring technical skills, while medical professionals bring the expertise required for semantic modeling. By combining expertise, we will develop hybrid AI models that accurately interpret medical accurately interpret medical data, leading to better healthcare outcomes.
