Galdeano: “Data Scientist covers a very wide field”
Íñigo Galdeano works as a Data Scientist at MMG. He is part of the Research and Development team at the Spanish start-up, which develops the semantic medical search engine based on Artificial Intelligence. Specifically, Galdeano is in charge of cleaning the data obtained from ontologies such as SNOMED so that they adapt to the models developed by the team to detect concepts in scientific texts.
“What we do is detect the concepts that we have previously extracted from different ontologies. My job is to transform the concepts in the best way so that the models we develop give the best results when it comes to processing the texts”, says the Data Scientist. Galdeano is also in charge of transferring the mathematical models to the code for increasing the productivity of the algorithm via API.
“Data Scientist is supposed to do a lot of things. It covers a very wide field,” says Galdeano.
“We are always thinking about the best way to detect these concepts,” acknowledges the data scientist, who is also an expert in Biomedical Engineering. In fact, he took a master’s degree at the Public University of Navarre after finishing his Technical Engineering in Telecommunications. “Biomedical Engineering encompasses all technology in the field of Medicine, from medical instruments to computer management,” he revealed.
Galdeano came to Biomedical Engineering because he was interested in signal and image processing. In fact, his master’s thesis focused on the application of photoplethysmography for the diagnosis of sleep apnea. “I wanted to see if the photoplethysmography signal could reliably detect sleep apnea events,” says Data Scientist, who subsequently went through a company that made predictive maintenance models of wind farms.
Later, he returned to the sanitary field. He participated in a study with Alzheimer’s patients at the University of Navarra Clinic. “Functional MRI measures cerebral blood perfusion in different areas. It was a comparative study in which conclusions could be drawn such as which parts of the brain are most involved in the evolution of the disease,” says Galdeano, who never thought he would end up devoting himself to Artificial Intelligence. “Little by little, I have been putting the focus.”