Interview with Rheumatologist and clinical immunologist: Judit Majnik and PhD student: Ádám Misák

International collaboration

Judit Majnik and Ádám Misák of Semmelweis University, the Hungarian member of the consortium, cite the international aspect and the complexity of the project as a motive to join. “It is exciting to see how scientists and clinicians of the same field but from different countries work together and also get to learn about their goals”, says Judit Majnik, a rheumatologist and clinical immunologist at Semmelweis University, and the Buda Hospital of the Hospitaller Order of Saint John of God, Budapest. “Working in international team is challenging but it’s a great way to use some of the know-how shared here in our daily practice.”

Ádám Misák and Judit Majnik

Personal motives

Forging new connections has been a main draw for Ádám Misák, a PhD student at the Department of Physiology at Semmelweis University, who has been involved in such work for the first time. “I wanted to experience what devising a project of this scale entails, what the legal and technical pitfalls are. And the only/best way to get an understanding of this is to get involved”, he says. “I have been mostly responsible for my own work, in this sense, managing a team for the first time is also a useful experience.” The complexity of the work could only be seen once inside, Majnik agrees. “Many questions/issues we would never expect to come up have arisen”, she adds.   

Besides personal motives, the reasons to get involved was to improve current practices. “Any tool that helps optimize patient referral to hospitals could support our work as clinicians considerably”, Majnik says. “If this work leads to tools that can categorize the patients we receive based on their issues or, further ahead, predict potential treatment options for them – even a small step forward of any of the above solutions could speed up patient journey, diagnostic accuracy and result in an overall more efficient workflow.”

Crucial Role of Data and AI in Revolutionizing Healthcare

When talking about the role of data in healthcare, it is the element of time that Majnik highlights as crucial. “It is not a question of whether patients have access to proper care; it is rather when they do. Wait times in healthcare can be long in every country but that could be rationalized by collecting and assessing data properly. A diagnostic tool could also help patients receive the right treatment more quickly”, she adds.

Misák mentions another aspect to digital revolution in health care. “Score charts in use in patient care are rather outdated when considering the amount of data available and the extent to which predictive methods have developed. Projects/apps like SPIDeRR could help streamline these systems for more effective use. Since the applying these tools is fairly similar, adaptation will not be a problem, according to the aspiring data scientist who was acquainted with programming and machine learning through a students’ scientific association at university. “I believe using AI-backed applications will be just as a positive experience as it is using the current ones.”