no code implementations • 10 May 2023 • Neslihan Bayramoglu, Martin Englund, Ida K. Haugen, Muneaki Ishijima, Simo Saarakkala
This study demonstrated the potential of machine learning models to predict the progression of PFOA using imaging and clinical variables.