no code implementations • 10 Apr 2023 • Andrew Wentzel, Carla Floricel, Guadalupe Canahuate, Mohamed A. Naser, Abdallah S. Mohamed, Clifton David Fuller, Lisanne van Dijk, G. Elisabeta Marai
Developing applicable clinical machine learning models is a difficult task when the data includes spatial information, for example, radiation dose distributions across adjacent organs at risk.
no code implementations • 4 Jul 2022 • Alessia De Biase, Nanna Maria Sijtsema, Lisanne van Dijk, Johannes A. Langendijk, Peter van Ooijen
Predictions were the closest to the ground truth at a probability threshold of 0. 9 (DSC of 0. 70 in the A, 0. 77 in the S, and 0. 80 in the C plane).
no code implementations • 5 Aug 2021 • Carla Floricel, Nafiul Nipu, Mikayla Biggs, Andrew Wentzel, Guadalupe Canahuate, Lisanne van Dijk, Abdallah Mohamed, C. David Fuller, G. Elisabeta Marai
Although cancer patients survive years after oncologic therapy, they are plagued with long-lasting or permanent residual symptoms, whose severity, rate of development, and resolution after treatment vary largely between survivors.
no code implementations • 25 Aug 2020 • Andrew Wentzel, Guadalupe Canahuate, Lisanne van Dijk, Abdallah Mohamed, Clifton David Fuller, G. Elisabeta Marai
Advances in data collection in radiation therapy have led to an abundance of opportunities for applying data mining and machine learning techniques to promote new data-driven insights.