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Scientific Reports|July 8, 2021
Oropharyngeal cancer patient stratification using random forest based-learning over high-dimensional radiomic featuresHarsh Patel, David M Vock, G Elisabeta Marai, et al.
Frontiers in Oncology|June 6, 2018
Exploring Applications of Radiomics in Magnetic Resonance Imaging of Head and Neck Cancer: A Systematic ReviewAmit Jethanandani, Timothy A Lin, Stefania Volpe, et al.
IEEE Visualization Conference : VIS. IEEE Conference on Visualization|September 12, 2024
Explainable Spatial Clustering: Leveraging Spatial Data in Radiation OncologyAndrew Wentzel, Guadalupe Canahuate, Lisanne V van Dijk, et al.
Proceedings. International Database Engineering and Applications Symposium|April 8, 2022
Predicting late symptoms of head and neck cancer treatment using LSTM and patient reported outcomesYaohua Wang, Lisanne Van Dijk, Abdallah S R Mohamed, et al.
Artificial Intelligence in Medicine. Conference on Artificial Intelligence in Medicine (2005- )|September 20, 2021
Identifying Symptom Clusters Through Association Rule MiningMikayla Biggs, Carla Floricel, Lisanne Van Dijk, et al.
Journal of Personalized Medicine|November 27, 2021
Dynamics-Adapted Radiotherapy Dose (DARD) for Head and Neck Cancer Radiotherapy Dose PersonalizationMohammad U Zahid, Abdallah S R Mohamed, Jimmy J Caudell, et al.
International Journal of Radiation Oncology, Biology, Physics|June 30, 2016
Spatial Precision in Magnetic Resonance Imaging-Guided Radiation Therapy: The Role of Geometric DistortionJoseph Weygand, Clifton David Fuller, Geoffrey S Ibbott, et al.
Proceedings. IEEE International Conference on Healthcare Informatics|February 12, 2024
Improving Prediction of Late Symptoms using LSTM and Patient-reported Outcomes for Head and Neck Cancer PatientsYaohua Wang, Lisanne Van Dijk, Abdallah S R Mohamed, et al.
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