Instructor, Radiation Oncology
Dana Farber Cancer Institute
Dr. Benjamin Kann's research is focused on the development and application of machine learning and neural networks for cancer imaging analysis and the development of digital biomarkers to predict clinical outcomes. He is interested in the use of artificial intelligence and cancer imaging to develop clinical decision-making tools that advance personalized cancer care and can be effectively translated into the clinic.
Radiology, Clinical Research
Harvard Medical School
Leveraging existing pediatric low-grade tumor specimens, clinical and imaging outcome data and artificial intelligence innovations to develop integrated biomarkers of response for children with low-grade glioma
This study will utilize artificial intelligence algorithms to predict underlying mutational status and outcomes for pediatric low grade glioma based on complex brain tumor MRI imaging features.
Benjamin H. Kann
Low-Grade Gliomas also called astrocytomas are the most common cancer of the central nervous system in children. They represent a heterogeneous group of tumors that can be discovered anywhere within the brain or spinal cord. Although surgical resection may be curative, up to 20% of children still su