Epidemiology and Biomedical Data Science: A Master’s degree ahead of its time

Medicine has evolved rapidly in time and again owing to epidemics or pandemics as well as the rapid mutation of diseases. If you too are from a health or medicine background, there are always lacunae we observe between the diagnosis, prescription and outcome, especially in developing countries. In epidemiology, we study health from diverse perspectives and transcribe these perspectives using quantitative methods and ideas.
A stream in a garden

My key motivations

I come from a background in clinical pharmacy and have worked on several clinical setups such as a hospital, government bodies, trials and others. In these setups, we have humongous data, however, it is futile if the information cannot do anything productive for humanity!

A commonality in all was the absence of high-end technological adaptability and the need for data analysis. In changing times, epidemiology cannot be studied in silos but rather in sync with other educational studies such as biology, social sciences, economics and others. Health, in many instances, cannot be studied using “Human Trials”, hence the need for epidemiology arises!

Humanity, at the moment, is technology-centric, as a result, health is also becoming technologically oriented.

This urged me to look into epidemiology and biomedical data science. Epidemiology is quantitative when studied from the perspective of the masses, however, the epidemiologist depends upon a data scientist to analyse the complete data. In a competitive world today, a skilled epidemiologist needs to be in a position to compute data not only theoretically but also using statistics and codes. It is largely this quantitative modus operandi that manifests in the day-to-day health of a person with an inclusive perspective of One-Health. This is where large data meets an individual life per diem.

What have I gained?

R-Programme, SPSS, Artificial intelligence, and Machine learning are the prerequisites of a data scientist. Nonetheless, it is your further interest that dives you deeper either as a data scientist or epidemiologist. Having a little of all these skills will take you ahead of others.

At several stances robots have been utilised already in anaesthesia. Soon, Robotics and AI will strengthen their hold on several other health-centric studies such as drug-delivery formulations, clinical trial analysis, oncology and oncoprotein and several other disciplines.

Why I chose Finland

As per World Bank Healthcare rankings, Finland stands at the 5th position in the world and as per World Intellectual Property Organization (UN), Finland is in the 7th position in the world for Global innovations. This is evident because the researchers collaboratively culminate cutting-edge outcomes in health and technology. Consequently, studying at a top-notch country providing a prodigious scholarship for Epidemiology and Biomedical Data Science at the University of Oulu became the right choice for me!

About the author

Khujith Rajueni, from India, is an aspiring epidemiologist and biomedical data scientist. His hobbies are yoga, music and reading. Apart from Finland's high sustainability and health standards, he enjoys the culture, nature and people in Finland.