In this short article, we focus on four dimensions of data that create layers of complexity using the data in the context of AI systems developed for medical applications collectively referred to as diagnostic medicine. These complexities, or ‘data dilemmas,’ share a core human element, making it clear why a human-centered approach is needed in understanding the relationship between medical data and AI systems.
