Dr. Ziemer brings the concepts of pattern recognition, knowledge-based automation, machine learning and highly quantitative/statistical methods to radiation therapy in order to improve patient outcomes, reduce normal tissue complications and reduce both inter-and intra- clinic variations.
His research is also focused on reducing inequities and biases present in medicine. He, along with a diverse set of collaborators, are developing clinical decision support tools to improve cancer care for those without access to robust health insurance plans and to make these tools available to rural centers that might not have access to medical innovations available in urban areas or those near large academic institutions.
He believes in forming collaborations to bring strong, dedicated minds together to study the vast, differentiated datasets to make progress in any one given individual’s struggle against cancer
