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Publicaties

Evaluation of a comprehensive set of normal tissue complication probability models for patients with head and neck cancer in an international cohort

International Expert-Based Consensus Definition, Classification Criteria, and Minimum Data Elements for Osteoradionecrosis of the Jaw: An Inter-Disciplinary Modified Delphi Study

MRI-Based Head and Neck Tumor Segmentation Using nnU-Net with 15-Fold Cross-Validation Ensemble

Multi-institutional Normal Tissue Complication Probability (NTCP) Prediction Model for Mandibular Osteoradionecrosis: Results from the PREDMORN Study

Normal tissue complication probability model predicting taste impairment in head and neck cancer patients: Evaluating the taste bud bearing tongue mucosa as a predictor

Optimal timing of organs-at-risk-sparing adaptive radiation therapy for head-and-neck cancer under re-planning resource constraints

PET and CT based DenseNet outperforms advanced deep learning models for outcome prediction of oropharyngeal cancer

Rising incidence of radiation pneumonitis after adjuvant durvalumab in NSCLC patients treated with concurrent chemoradiotherapy

The prognostic value of pathologic lymph node imaging using deep learning-based outcome prediction in oropharyngeal cancer patients

Three-Dimensional Deep Learning Normal Tissue Complication Probability Model to Predict Late Xerostomia in Patients With Head and Neck Cancer