Researchers from the ITACA Institute at the Universitat Politècnica de València (UPV) have been awarded the Best Paper Award at the 8th International Workshop on Process-Oriented Data Science for Healthcare (PODS4H25), held in Montevideo (Uruguay).
This international recognition highlights the excellence and impact of the team’s work in the field of artificial intelligence applied to clinical data analysis.
The study, titled “Extraction and Identification of Medications from EHR Notes with LLMs: A Tool and a Case Study”, was developed by Carlos Fernández-Llatas and Alejandro Gómez-Noé (SABIEN-ITACA), in collaboration with Begoña Martínez-Salvador and Mar Marcos from the Universitat Jaume I.
Artificial intelligence to read medical records
The study proposes an innovative tool based on Large Language Models (LLMs) —the same technology that powers systems such as ChatGPT— capable of automatically extracting information about medications mentioned in clinical notes from Electronic Health Records (EHRs).
This data extraction is key to advancing healthcare process mining, a discipline that analyses hospital workflows to optimise patient care.
“Until now, this task required a great deal of time and resources, since medical texts are usually written in free language, often containing abbreviations, mistakes or even several languages. Thanks to this new methodology, we have managed to automate and speed up the process, while also ensuring patient data privacy,” explains Alejandro Gómez, researcher at the ITACA Institute – UPV.
The approach was validated in a case study involving patients with chronic obstructive pulmonary disease (COPD), demonstrating that the results can be successfully integrated into process mining tools to analyse and improve workflows in hospitals and healthcare centres.
International recognition of the leadership of the SABIEN-ITACA group
The PODS4H25 conference is one of the most prominent international events in the field of process mining applied to healthcare. Its aim is to bring together researchers and professionals to share advances that enhance the efficiency, safety and quality of medical care through the use of real data.
The award obtained by the ITACA-UPV team represents a major international acknowledgement of the leadership of the SABIEN group in applying artificial intelligence and data science to improve management and decision-making in health systems.
“Our goal is to help healthcare professionals make the most of the information available in medical records to make better-informed decisions and improve patient care,” concludes Fernández-Llatas, principal investigator of the study.