P. Kalendralis
Recent publications
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de Zegher, I., Norak, K., Steiger, D., Mueller, H., Kalra, D., Scheenstra, B., Cina, I., Shulz, S., Uma, K., Kalendralis, P., Lotmam, E.-M., Benedikt, M., Dumontier, M., & Celebi, R. (2024). Artificial intelligence based data curation: enabling a patient-centric European health data space. Frontiers in medicine, 11, Article 1365501. https://doi.org/10.3389/fmed.2024.1365501More information about this publication
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Kalendralis, P., Luk, S. M. H., Kalet, A. M., Piotrowski, T., Ryczkowski, A., Kazmierska, J., Bermejo, I., & Dekker, A. (2024). External validation of an AI tool for the detection of radiotherapy errors- A multicentric study. Radiotherapy and Oncology, 194, S4752-S4753.More information about this publication
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Piotrowski, T., Ryczkowski, A., Kalendralis, P., Adamczewski, M., Sadowski, P., Bajon, B., Kruszyna-Mochalska, M., & Jodda, A. (2024). Forecasting model for qualitative prediction of the results of patient-specific quality assurance based on planning and complexity metrics and their interrelations. Pilot study. Reports of Practical Oncology and Radiotherapy, 29(3), 318-328. https://doi.org/10.5603/rpor.101093More information about this publication
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Kalendralis, P., Luk, S. M., Canters, R., Eyssen, D., Vaniqui, A., Wolfs, C., Murrer, L., van Elmpt, W., Kalet, A. M., Dekker, A., van Soest, J., Fijten, R., Zegers, C. M., & Bermejo, I. (2023). AI-based radiotherapy treatment planning quality assurance: A multi-institutional study. Radiotherapy and Oncology, 182, S243-S244.More information about this publication
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Hasannejadasl, H., Roumen, C., van der Poel, H., Vanneste, B., van Roermund, J., Aben, K., Kalendralis, P., Osong, B., Kiemeney, L., Van Oort, I., Verwey, R., Hochstenbach, L., J Bloemen-van Gurp, E., Dekker, A., & Fijten, R. R. R. (2023). Development and external validation of multivariate prediction models for erectile dysfunction in men with localized prostate cancer. PLOS ONE, 18(3), Article e0276815. https://doi.org/10.1371/journal.pone.0276815More information about this publication
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Kalendralis, P., Luk, S. M. H., Canters, R., Eyssen, D., Vaniqui, A., Wolfs, C., Murrer, L., van Elmpt, W., Kalet, A. M., Dekker, A., van Soest, J., Fijten, R., Zegers, C. M. L., & Bermejo, I. (2023). Automatic quality assurance of radiotherapy treatment plans using Bayesian networks: A multi-institutional study. Frontiers in Oncology, 13(1), Article 1099994. https://doi.org/10.3389/fonc.2023.1099994More information about this publication
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Swart, R. R., Fijten, R., Boersma, L. J., Kalendralis, P., Behrendt, M. D., Ketelaars, M., Roumen, C., & Jacobs, M. J. G. (2023). External validation of a prediction model for timely implementation of innovations in radiotherapy. Radiotherapy and Oncology, 179(1), Article 109459. https://doi.org/10.1016/j.radonc.2022.109459More information about this publication
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Kalendralis, P., Sloep, M., Choudhury, A., Seyben, L., Snel, J., George, N. M., Veugen, J., Veening, M., Langendijk, J. A., Dekker, A., van Soest, J., & Fijten, R. (2023). Technical note: A knowledge graph approach to registering tumour specific data of patient-candidates for proton therapy in the Netherlands. Medical Physics, 50(2), 1044-1050. https://doi.org/10.1002/mp.16105More information about this publication
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Kalendralis, P., Vallières, M., Kann, B. H., Sanjay, A., Rashid, A. S., Dekker, A., & Fijten, R. (2023). Radiomics: "unlocking the potential of medical images for precision radiation oncology". In J. Kang, T. Rattay, & B. S. Rosenstein (Eds.), Machine Learning and Artificial Intelligence in Radiation Oncology: A Guide for Clinicians (pp. 73-105). Elsevier. https://doi.org/10.1016/B978-0-12-822000-9.00009-4More information about this publication
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Kalendralis, P., Sloep, M., Snel, J., George, N. M., Langendijk, J. A., Veening, M., Dekker, A., van Soest, J., & Fijten, R. (2022). The Dutch Initiative for the Model-Based Selection of Patients for Proton Therapy - A Federated Learning IT Infrastructure. International Journal of Radiation Oncology Biology Physics, 114(3), S19-S19. https://doi.org/10.1016/j.ijrobp.2022.07.366More information about this publication