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Nanna Maria Sijtsema

Showing results (1-10 of 7) with videos related to

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Frontiers in Oncology|June 25, 2026
Editorial: Artificial intelligence advancing lung cancer screening and treatmentSunyi Zheng, Nanna Maria Sijtsema, Chunliang Wang, et al.
BJR Artificial Intelligence|May 1, 2026
Clinical adoption of deep learning target auto-segmentation for radiation therapy: challenges, clinical risks, and mitigation strategiesAlessia De Biase, Nanna Maria Sijtsema, Tomas Janssen, et al.
Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society|April 2, 2025
Uncertainty-aware deep learning for segmentation of primary tumor and pathologic lymph nodes in oropharyngeal cancer: Insights from a multi-center cohortAlessia De Biase, Nanna Maria Sijtsema, Lisanne V van Dijk, et al.
Computers in Biology and Medicine|May 31, 2024
Probability maps for deep learning-based head and neck tumor segmentation: Graphical User Interface design and testAlessia De Biase, Liv Ziegfeld, Nanna Maria Sijtsema, et al.
Frontiers in Oncology|September 4, 2023
Editorial: Application of radiomics in understanding tumor biological behaviors and treatment responseNingping Xiao, Zhengda Pei, Wenhui Lu, et al.
Radiotherapy and Oncology : Journal of the European Society for Therapeutic Radiology and Oncology|May 3, 2024
Late-xerostomia prediction model based on <sup>18</sup>F-FDG PET image biomarkers of the main salivary glandsYan Li, Maria Irene van Rijn-Dekker, Suzanne Petronella Maria de Vette, et al.
Radiotherapy and Oncology : Journal of the European Society for Therapeutic Radiology and Oncology|January 7, 2023
Validation of the <sup>18</sup>F-FDG PET image biomarker model predicting late xerostomia after head and neck cancer radiotherapyYan Li, Nanna Maria Sijtsema, Suzanne Petronella Maria de Vette, et al.
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Showing results (1-10 of 7) with videos related to

Sort By:
Pageof 1
Frontiers in Oncology|June 25, 2026
Editorial: Artificial intelligence advancing lung cancer screening and treatmentSunyi Zheng, Nanna Maria Sijtsema, Chunliang Wang, et al.
BJR Artificial Intelligence|May 1, 2026
Clinical adoption of deep learning target auto-segmentation for radiation therapy: challenges, clinical risks, and mitigation strategiesAlessia De Biase, Nanna Maria Sijtsema, Tomas Janssen, et al.
Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society|April 2, 2025
Uncertainty-aware deep learning for segmentation of primary tumor and pathologic lymph nodes in oropharyngeal cancer: Insights from a multi-center cohortAlessia De Biase, Nanna Maria Sijtsema, Lisanne V van Dijk, et al.
Computers in Biology and Medicine|May 31, 2024
Probability maps for deep learning-based head and neck tumor segmentation: Graphical User Interface design and testAlessia De Biase, Liv Ziegfeld, Nanna Maria Sijtsema, et al.
Frontiers in Oncology|September 4, 2023
Editorial: Application of radiomics in understanding tumor biological behaviors and treatment responseNingping Xiao, Zhengda Pei, Wenhui Lu, et al.
Radiotherapy and Oncology : Journal of the European Society for Therapeutic Radiology and Oncology|May 3, 2024
Late-xerostomia prediction model based on <sup>18</sup>F-FDG PET image biomarkers of the main salivary glandsYan Li, Maria Irene van Rijn-Dekker, Suzanne Petronella Maria de Vette, et al.
Radiotherapy and Oncology : Journal of the European Society for Therapeutic Radiology and Oncology|January 7, 2023
Validation of the <sup>18</sup>F-FDG PET image biomarker model predicting late xerostomia after head and neck cancer radiotherapyYan Li, Nanna Maria Sijtsema, Suzanne Petronella Maria de Vette, et al.
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