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DATAETHICS 2 DATAETHICS 2: The Ethics of Artificial Intelligence in Biomedicine is a Course

DATAETHICS 2: The Ethics of Artificial Intelligence in Biomedicine

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Digitalization is a key initiative in everyday life, including healthcare. Within this, one of the most promising and disruptive technologies is Artificial Intelligence (AI). AI has started to play an increasingly important role in daily medical practice. AI agents have already shown that they can match or even outperform human professionals in determining the best treatments for, amongst others, cancer patients. However, as new data science and AI technologies are being developed and tested, concerns have arisen regarding their ethical, societal and legal implications, as well as their susceptibility to errors. These include issues concerning clinical accuracy and safety, transparency, security, accountability, data privacy and fairness.

This e-course offers a unique set of lectures and exercise enabling you to familiarize yourself with the value chain of ethical, social and legal considerations in the field of biomedical AI solutions.

With this e-course, you will learn about the fundamentals of coupling and implementing biomedical AI and data management. The lectures framed around a dilemma story based on a real-life case study, will offer you the basis to analyse, categorise and address key ethical considerations of AI in biomedicine and understand how to address AI/ML models in (bio)medical practice. You will develop understanding on how to assess the use of Biomedical Big Data in the context of the ethical implications that inevitably follow it, and how to leverage ethical consideration in decision making. Participation in this course will foster your transversal skills and equip you with cutting edge knowledge on big data relevant to your study, research or internships.

The expertise of the speakers covers a broad spectrum of research and application interests from bioethics, health policy and social studies of medicine, to cutting-edge genomics, analysis of large heterogeneous high-throughput data-sets and AI solutions for biomedicine.

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