Ernestina Menasalvas. 
Full Professor at the ETSI-Technical University of Madrid (UPM) and head of the Data Mining and Simulation Research Group (MIDAS)

What is the role of the UPM within the Clarify project? What goals do you expect to achieve?

UPM oversees the tasks responsible of: i) transforming by natural language processing clinical notes into a structured database, ii) clean and semantically enrich the database, iii) apply machine learning algorithms to extract knowledge and patterns. 

The main goal behind this task is to find patterns to stratify patients by risk, find factors that help predict relapses and/or increase survival rates.

How can Big Data help us within the healthcare field?

All the data being collected for each patient can now be integrated and tools can be developed to help physicians in the decision-making process.

By integrating data coming from heterogenous databases, cleaning, preparing and using them to extract patterns Big data will help towards evidence-based medicine.

Are Spanish companies and organizations making use of Big Data in their activity? What would still need to be improved? 

Big Data/data science technologies are being adopted by companies of all sizes and sectors. The main challenge however is on the one hand finding data scientist with the appropriate skills. Companies and academy must jointly work to produce professionals that can help implementing the tools to extract value out of the data. 

Do you think they are missing opportunities or could be more creative?

We are producing data in all sectors that could be used to innovate and improve activities in all sectors. The challenge is to count with the multidisciplinary team business/data scientists to spot the opportunity and transform data into value.

How did you get specialized in this area?

I am computer scientist and started working with data and knowledge discovery from data since I finished my studies. I have always liked working in real problems analysing needs and trying to produce data driven solutions that can help to improving the society. 20 years ago, this was not the hype that is today. Maybe, the hype will go, but no doubt that still data will hide knowledge and it will be worth investing time in helping to find this knowledge to improve life in one or another way.

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