On July 22, Tiago Miranda, research technician, presented a poster at the Lisbon Machine Learning School (LxMLS) 2025 entitled “Inferring diagnostics from prescription data: a machine learning approach”.
The work, developed within the scope of the HealthDisrupt project, aims to infer disease diagnoses by analyzing patterns in medical prescriptions. The research team used electronic prescription records (EPRs) and Natural Language Processing (NLP) methods to estimate disease prevalence based on the data. The HealthDisrupt project is funded by the FCT through the call “Artificial Intelligence, Data Science and Cybersecurity relevant to Public Administration.”