Course on AI and Big Data prepares students for the future of medicine

“Big Data and AI in clinical healthcare” course was held for the eighth year in a row, bringing together an interdisciplinary group of students and experts to discuss the significance of artificial intelligence and big data in medicine.

The usage artificial intelligence (AI), machine learning technologies and large amounts of data is inevitably becoming an important part of healthcare. To ensure the proper validation and adaptation of these tools, medical students, students from other related fields, and other healthcare professionals need to be trained to understand these aspects. For this reason, the University of Helsinki organizes a course called “Big Data and AI in clinical healthcare”, which aims to increase the critical understanding of these new concepts and offer practical examples of their use in modern medicine. Now in the spring of 2024, the course was organized for the 8th time.

The course consisted of expert lectures from e.g. HUS, University of Helsinki, and Aalto University, covering comprehensively various aspects of artificial intelligence and big data. Some lecturers were also involved in AI-related flagship projects, such as iCAN and FCAI. The focus was especially on practical applications of AI in fields such as medical imaging, cancer treatment, and brain research. Additionally, discussions during the lectures focused on the impact of AI on empathy, as well as ethical issues and concerns associated with the use of such technology. The lectures were always followed by interactive discussion and group work, where the students were divided into interdisciplinary teams to evaluate scientific articles on artificial intelligence applications in medicine. 

Beyond the hype: introducing students to the ordinary side of AI

The University of Helsinki already offers training in the basics of machine learning, but otherwise there have been no courses targeted for students of medicine or biomedicine with concrete examples of the impact of these technologies in healthcare before this course. 

The course is run by Vilja Pietiäinen, a docent in cellular and molecular biology from Institute for Molecular Medicine Finland, University of Helsinki, together with Jussi Merenmies, director of the medical education program and clinical instructor at University of Helsinki. Pietiäinen sees that one of the goals of the course is to familiarize students with the entire field of AI in healthcare and this way demonstrate that, despite the hype, much of it is quite ordinary, and some aspects of AI are already used in clinical medicine as well as in our everyday life.

One of the guest lecturers was Katri Saarikivi, a brain researcher from the field of cognitive neuroscience focusing especially on empathy and interaction. "The entire course is an important, timely overview of technological developments and their possibilities and impacts from a medical perspective”, says Saarikivi. “In my opinion, it introduces students to various topics worth following in their own work and ways to think about the future of their profession."

Students see AI as an inevitable part of their future career

When talking with the course participants, it is clear that students from different fields believe that artificial intelligence will be part of their future work. "AI will certainly be used in many different tasks in our future careers, especially if AI tools will be utilized in future medical practices. This course provides a kind of early warning of what to expect," reflects medical student Samu Huovinen.

Oskar Kopra, a second-year student of medicine and computer science, was interested in the course to combine his two study fields: “This course is the only opportunity where medical studies are integrated with artificial intelligence.”

Kopra is particularly interested in current and future applications of AI. Many other participants mention that the best part of the course was gaining a deeper understanding of the mechanisms behind AI. Additionally, students appreciate hearing experts' deeper insights on the topic, rather than just what is heard in the media.

"For a big part, participating in the course is just to satisfy my own curiosity. But in terms of research, the learnings gained from the course are fascinating, and based on this, students might become interested in joining a research group after getting a good introduction in the field here", Kopra says.

Exploring the impact of AI across disciplines

The course was originally established only for medical students, but later it has also been opened for undergraduate students from related fields as well as doctoral researchers. Now, another aim of the project is to train an interdisciplinary group of future experts for implementation of machine learning and big data in health care. Having students from multiple fields is hoped to strengthen the interaction and understanding between medical students and students from other disciplines.

Vilja Pietiäinen explains that the current goal is to "bring together students and graduates from different fields and stages of study, as interdisciplinary collaboration is needed in future AI development. We want to enable interaction between organizers, speakers, and interdisciplinary students."