 The study aims to investigate the factors influencing the adoption process of machine learning, ML, systems for medical diagnostics in clinics, and develop a maturity model that can help practitioners assess their current state in the ML adoption process. The study identifies 13 ML specific factors that influence the adoption process, categorized into seven domains forming a holistic ML adoption framework for clinics. This article was authored by Luisa Pumplin, Mariska Fecho, Nihal Wall, and others.