Vaneza Gómez arrived in Barcelona from Bogotá (Colombia) a year and a half ago, after winning a scholarship to complete her undergraduate studies at the Polytechnic University of Catalonia and graduate in Biomedical Engineering. Now, at 23 years old, she has just successfully submitted her final degree thesis, in which he used the knowledge she acquired during her internship and current work at the Artificial Intelligence Area of the TIC Salut Social Foundation.
Because it is a degree that really suited my preferences: mathematics, exact sciences and human sciences, mechanics and medicine. It is pretty much everything I want to learn in my life! I graduated from three universities on the same degree course: the Polytechnic University of Catalonia in Barcelona, the University of Rosario and the Julio Garavito Colombian Engineering School in Bogotá, Colombia.
My work consisted of the generating synthetic electroencephalography (EEG) signals to train automatic learning models to detect Parkinson’s disease. I chose this topic because analysing and processing medical signals and images is an area that I really enjoyed while studying for my degree. During my internship at the TIC Salut Social Foundation, I also worked with synthetic data and wanted to go deeper into that.
In my work I managed to generate synthetic EEG signals that are a valid representation of the real signals for both control patients and patients with Parkinson’s disease. I also managed to train a machine learning model for disease detection from EEG signals with an accuracy of 97.88% in real signals and 84% in synthetic signals. These results would not have been possible without the knowledge of synthetic data and machine learning that I acquired during the internship and the support of Susanna Aussó and Didier Domínguez, my thesis tutors at the TIC Salut Social Foundation.
My current work still focusses on creating tabular and relational synthetic medical data. I am trying to improve these techniques and am testing new tools. My experience at the Artificial Intelligence Area is very enriching and I am learning incredible things!
In the future I would like to continue working in the field of Artificial Intelligence applied to health to provide optimal computational solutions to teams of health professionals and researchers.
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