LAUSR

Clinical Practice Guidelines (CPGs) aim at improving the quality of health care by providing standardized best practices for diagnosis and treatment. However, physicians have difficulties to understand the (often implicit) rationale underlying expert recommendations. The aim of this paper is to propose an approach based on preference learning for building a model that is closest to the reasoning of experts to provide recommendations. We apply this method to antibiotherapy in primary care. The preference model was learned from the recommendations and from a database describing the domain.