Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Hendrike Neh

Showing results (1-10 of 4) with videos related to

Pageof 1
Sort By:
Medical Physics|July 21, 2021
Assessment of a diaphragm override strategy for robustly optimized proton therapy planning for esophageal cancer patientsSabine Visser, Hendrike Neh, Cássia Oraboni Ribeiro, et al.
International Journal of Radiation Oncology, Biology, Physics|August 15, 2024
Three-Dimensional Deep Learning Normal Tissue Complication Probability Model to Predict Late Xerostomia in Patients With Head and Neck CancerHung Chu, Suzanne P M de Vette, Hendrike Neh, et al.
Physics and Imaging in Radiation Oncology|May 8, 2026
An evaluation of uncertainty quantification methods and measures for deep learning outcome prediction models in head and neck cancer radiotherapyDaniel C MacRae, Luuk van der Hoek, Joëlle E van Aalst, et al.
Oral Oncology|March 2, 2025
Evaluation of a comprehensive set of normal tissue complication probability models for patients with head and neck cancer in an international cohortSuzanne P M de Vette, Maria I van Rijn-Dekker, Lisa Van den Bosch, et al.
Pageof 1

Showing results (1-10 of 4) with videos related to

Sort By:
Pageof 1
Medical Physics|July 21, 2021
Assessment of a diaphragm override strategy for robustly optimized proton therapy planning for esophageal cancer patientsSabine Visser, Hendrike Neh, Cássia Oraboni Ribeiro, et al.
International Journal of Radiation Oncology, Biology, Physics|August 15, 2024
Three-Dimensional Deep Learning Normal Tissue Complication Probability Model to Predict Late Xerostomia in Patients With Head and Neck CancerHung Chu, Suzanne P M de Vette, Hendrike Neh, et al.
Physics and Imaging in Radiation Oncology|May 8, 2026
An evaluation of uncertainty quantification methods and measures for deep learning outcome prediction models in head and neck cancer radiotherapyDaniel C MacRae, Luuk van der Hoek, Joëlle E van Aalst, et al.
Oral Oncology|March 2, 2025
Evaluation of a comprehensive set of normal tissue complication probability models for patients with head and neck cancer in an international cohortSuzanne P M de Vette, Maria I van Rijn-Dekker, Lisa Van den Bosch, et al.
Pageof 1