“Using data science in research will enable you to get the most out of your data,” says Jonas Isaksen, postdoctoral fellow with the Department of Biomedical Sciences, University of Copenhagen.

Data science, including artificial intelligence and machine learning, is under great development and researchers are starting to use these tools.

“First of all, data science enables you to analyze large datasets and secondly you will have an unbiased analysis,”

says Jonas Isaksen who is a biomedical engineer by training and today works with data science as a means to improve ECG-analysis.

You gain unbiased results

Jonas Isaksen continues to explain that the advantage of using an unbiased data model is that it does not know how you usually analyze e.g. an MRI-scan. Thus, using data science gives you the chance of getting results that you did not expect. In the opinion of Jonas Isaksen, data science and artificial intelligence (AI) are especially useful when analyzing complex, picture-like data such as ECG, MRI, CT, and ultrasounds as the AI-model will learn to analyze each problem anew as if it had never seen such data before.

You need understanding and key concepts

Some basic knowledge is needed before setting out to use data science.

“Just hiring a data scientist for an analysis task rarely brings fruitful results. You need to speak a common language"

Thus, you should strive to gain a basic understanding of key concepts in order to participate in the overall design of a data analysis and the interpretation of the results,” says Jonas Isaksen.

At University of Copenhagen and in cooperation with DCAcademy, Jonas Isaksen is organizing a course in data science for non- data scientists 17 - 18 August 2023. The aim is to give the participants the prerequisites to start working with data science. They will get the ability to identify data science aspects of their own research and an introduction to the most important concepts.

A PhD Cardiovascular Winter School at University of Copenhagen will also dedicate an entire day (12 January 2023) to data science. Stay informed on these events at our website.