Workshop 10

Challenges of Digitalization within Modern Health Systems (CD-MHS)

Workshop Description:

Modern technologies such as Artificial intelligence (AI) and Machine Learning (ML) are revolutionizing modern health systems, offering transformative potential to enhance patient care, improve clinical decision-making upon automated diagnosis tools, and to augment and improve healthcare operations. Participants will present and discuss various aspects of healthcare, from human-medicine to veterinary medicine and their interconnection with the environment, as stated in the “One Health” paradigm. In fact, for modern health systems, in addition to medical aspects also legal, technical, ethical, and socioeconomic aspects are of relevance, making the topic highly interdisciplinary.

Thus, the topics of the workshop include but are not limited to:

  • Prediction, prevention, and management of future pandemic threats
  • Legal and ethical aspects of digital methods in medicine
  • Medical data visualization
  • Communications system
  • Storing and analyzing medical data
  • Public health surveillance
  • Tele-medicine & Connected Health
  • AI in healthcare
  • Data privacy, algorithmic fairness in digital health

Target Audience:

Healthcare professionals, healthcare administrators, AI researchers, policymakers, and anyone interested in the intersection of AI, digital health, eHealth and modern health systems.

Workshop Format:

The workshop will employ a variety of engaging learning methods, including:

  • Expert presentations: Leading experts in AI and healthcare will provide in-depth presentations on various areas of digital health.
  • Interactive discussions: Participants will engage in facilitated discussions to explore the ethical considerations, challenges, and strategies for responsible systems.

Invited Speakers:

Assoc.-Prof. Amélie Desvars-Larrive, DVM is currently associate professor of Infectious Disease Epidemiology at the University of Veterinary Medicine Vienna, Austria, and resident scientist at Complexity Science Hub Vienna. Her current research bridges field epidemiology and data science, with a primary focus on zoonotic and emerging diseases, prioritizing applied research and One Health approaches.

Call for Participation:

We would like to invite the attendants to submit extended abstracts of original research or literature reviews highlighting the proposed workshop theme regarding the exploration of how Artificial Intelligence & Machine Learning will impact Health Systems. From the extended abstracts submitted a maximum of seven will be selected for presentation. The presentations should take up to seven minutes to present their abstracts to the workshop.

Submission Information:

To submit an extended abstract to our AIRoV 2024 workshop on “Challenges of Digitalization within Modern Health Systems,” begin by drafting a concise yet comprehensive document, typically between 1,000 to 1,500 words. Your abstract should clearly outline the core aspects of your research or findings, focusing specifically on how they relate to the digitization challenges in modern health systems.

Please include the following: an introduction, a brief literature review, your methodology, primary findings, and the implications of your work.

Ensure that your abstract adheres to the formatting and submission guidelines provided by the conference, which often include specific requirements for font size, style, and document format.

The deadline for submissions is 31 January 2024.

Post Workshop:

The results and insights generated during the workshop are invaluable, and we are committed to sharing them with a larger audience to foster broader understanding and impact. We will publish the proceedings to disseminate the extended abstracts.


  • Dr. Mark A.M. Kramer - vetmeduni
  • Dipl. Ing. Christian Walter - vetmeduni
  • Anna Pontel DVM. MSc. - vetmeduni