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Deep learning-based outcome prediction using PET/CT and automatically predicted probability maps of primary tumor in patients with oropharyngeal cancer.
De Biase A, Ma B, Guo J, van Dijk LV, Langendijk JA, Both S, van Ooijen PMA, Sijtsema NM. De Biase A, et al. Among authors: van dijk lv, van ooijen pma. Comput Methods Programs Biomed. 2024 Feb;244:107939. doi: 10.1016/j.cmpb.2023.107939. Epub 2023 Nov 22. Comput Methods Programs Biomed. 2024. PMID: 38008678 Free article.
Comparison of computed tomography image features extracted by radiomics, self-supervised learning and end-to-end deep learning for outcome prediction of oropharyngeal cancer.
Ma B, Guo J, Chu H, van Dijk LV, van Ooijen PMA, Langendijk JA, Both S, Sijtsema NM. Ma B, et al. Among authors: van dijk lv, van ooijen pma. Phys Imaging Radiat Oncol. 2023 Nov 7;28:100502. doi: 10.1016/j.phro.2023.100502. eCollection 2023 Oct. Phys Imaging Radiat Oncol. 2023. PMID: 38026084 Free PMC article.
Three-Dimensional Deep Learning Normal Tissue Complication Probability Model to Predict Late Xerostomia in Patients With Head and Neck Cancer.
Chu H, de Vette SPM, Neh H, Sijtsema NM, Steenbakkers RJHM, Moreno A, Langendijk JA, van Ooijen PMA, Fuller CD, van Dijk LV. Chu H, et al. Among authors: van ooijen pma. Int J Radiat Oncol Biol Phys. 2025 Jan 1;121(1):269-280. doi: 10.1016/j.ijrobp.2024.07.2334. Epub 2024 Aug 13. Int J Radiat Oncol Biol Phys. 2025. PMID: 39147208 Free PMC article.
174 results