Invited talk

We are very happy that Professor Ernestina Menasalvas Ruiz will give an invited talk at the thirteenth BioASQ workshop.

Title: From Clinical Notes to Clinical Insights: Leveraging LLMs for Structured Extraction, Normalization, and Decision Support in Healthcare

Speaker: Ernestina Menasalvas Ruiz, Universidad Politécnica de Madrid (UPM)

Abstract: The increasing availability of electronic medical records (EMRs) offers unprecedented opportunities to enhance clinical decision-making. However, these records are often unstructured, heterogeneous, and challenging to interpret. In this talk, the pipeline we use for extracting meaningful information from clinical notes using large language models (LLMs) and other NLP techniques will be presented. We will focus on entity extraction and normalization of medical terms to standard vocabularies. Our latest developments integrate this structured knowledge with conversational AI tools to build intelligent assistants that can support clinicians in their practice. These systems are designed to be privacy-preserving, adaptable to various clinical settings, and aligned with healthcare interoperability standards. In the talk different real-world applications with their challenges will be analyzed together with future research.

Biosketch: Ernestina Menasalvas Ruiz is a full professor at the Department of Computer Science, Universidad Politécnica de Madrid (UPM), where she also leads the MIDAS research group (focused on Data Analysis) at the Center for Biotechnology. She earned her PhD in Computer Science from UPM (1994). Her research spans over 25 years, specializing in data mining, big data analytics, and artificial intelligence, with a strong focus on extracting and analyzing unstructured medical data—especially clinical narratives—for healthcare insights. She has led and contributed to numerous EU-funded projects, including IASIS, Uncover, BigMedilytics, Clarify, and LUCIA. Ernestina has published over 40 peer‑reviewed articles in high‑impact journals such as Data & Knowledge Engineering, Information Sciences, Expert Systems with Applications, and Journal of Medical Systems. Her work is distinguished by its combination of rigorous theoretical methods with real-world applications in health, industry, and social web analytics.