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L. van der Hoek

affiliation not provided to SSRN

  • affiliation not provided to SSRN

SCHOLARLY PAPERS

5

DOWNLOADS

116

TOTAL CITATIONS

0

Scholarly Papers (5)

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1.

A multi-toxicity deep learning approach for normal tissue complication probability modelling in head and neck cancer patients receiving radiotherapy

Number of pages: 46 Posted: 16 Dec 2025 Last Revised: 26 May 2026
D.C. MacRae, L. van der Hoek, Suzanne Petronella Maria de Vette, Hendrike Neh, A Moreno, Clifton D. Fuller, Johannes A. Langendijk, Matias Valdenegro-Toro, Nanna M. Sijtsema, Peter M.A. van Ooijen and Lisanne van Dijk
University of Groningen - Department of Radiation Oncology, affiliation not provided to SSRN, University of Groningen - University Medical Center Groningen, University of Groningen - University Medical Center Groningen, University of Texas at Houston - MD Anderson Cancer Center, University of Texas at Houston - MD Anderson Cancer Center, University of Groningen, University of Groningen, University of Groningen - Department of Radiation Oncology, University of Groningen - University Medical Center Groningen and University of Texas at Houston - MD Anderson Cancer Center
Downloads 37 (1,263,436)

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Multi-toxicity, Normal Tissue Complication Probability, Deep learning, Radiotherapy, Aspiration, Dysphagia, Sticky saliva, Taste alteration, Xerostomia

2.

An Evaluation of Uncertainty Quantification Methods and Measures for Deep Learning Outcome Prediction Models in Head and Neck Cancer Radiotherapy

Number of pages: 20 Posted: 15 Jan 2026
D.C. MacRae, L. van der Hoek, Joëlle van Aalst, Suzanne Petronella Maria de Vette, Robert van der Wal, Hendrike Neh, Baoqiang Ma, Nanna M. Sijtsema, Matias Valdenegro-Toro, Peter M.A. van Ooijen and Lisanne van Dijk
University of Groningen - Department of Radiation Oncology, affiliation not provided to SSRN, affiliation not provided to SSRN, University of Groningen - University Medical Center Groningen, affiliation not provided to SSRN, University of Groningen - University Medical Center Groningen, University of Groningen - University Medical Center Groningen, University of Groningen - Department of Radiation Oncology, University of Groningen, University of Groningen - University Medical Center Groningen and University of Texas at Houston - MD Anderson Cancer Center
Downloads 29 (1,332,057)

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outcome prediction, deep learning, Uncertainty Quantification, NTCP, TCP

3.

Post-Radiotherapy Health Utility and Symptom Trends in Patients with Non-Metastatic Head and Neck Cancer

Number of pages: 20 Posted: 17 Dec 2025
Diego Larrotta-Castillo, Yi Hsuan Chen, L. van der Hoek, Bram Ramaekers, Brenda Leeneman, Carin Uyl-de Groot, Johannes A. Langendijk and Hedwig M. Blommestein
affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, Erasmus University Rotterdam (EUR), University of Groningen and VU University Amsterdam
Downloads 19 (1,459,862)

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Head and neck cancer, radiotherapy, Health-Related Quality of Life, EQ5D, Toxicity

4.

3D deep learning-based NTCP prediction model for radiation pneumonitis in locoregionally advanced-staged lung cancer patients

Number of pages: 18 Posted: 24 Apr 2026
Robert van der Wal, L. van der Hoek, Luis Ricardo DelaO-Arevalo, D.C. MacRae, Olga Chouvalova, Johannes A. Langendijk, Nanna M. Sijtsema, Peter M.A. van Ooijen, Robin Wijsman and Lisanne van Dijk
affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, University of Groningen - Department of Radiation Oncology, affiliation not provided to SSRN, University of Groningen, University of Groningen - Department of Radiation Oncology, University of Groningen - University Medical Center Groningen, University of Groningen - University Medical Center Groningen and University of Texas at Houston - MD Anderson Cancer Center
Downloads 17 (1,481,165)

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Radiation pneumonitis, Radiotherapy, Deep learning, Lung cancer, Toxicity, Machine learning, Normal tissue complication probability.

5.

Deep Learning Ntcp Model for Late Dysphagia after Radiotherapy for Head and Neck Cancer Patients Based on 3d Dose, Ct and Segmentations

Number of pages: 25 Posted: 17 Jul 2025
Suzanne Petronella Maria de Vette, Hendrike Neh, L. van der Hoek, D.C. MacRae, Hung Chu, Agata Bannink-Gawryszuk, Roel J.H.M. Steenbakkers, Peter M.A. van Ooijen, Clifton D. Fuller, Katherine A. Hutcheson, Johannes A. Langendijk, Nanna M. Sijtsema and Lisanne van Dijk
University of Groningen - University Medical Center Groningen, University of Groningen - University Medical Center Groningen, affiliation not provided to SSRN, University of Groningen - Department of Radiation Oncology, University of Groningen - University Medical Center Groningen, affiliation not provided to SSRN, University of Groningen, University of Groningen - University Medical Center Groningen, University of Texas at Houston - MD Anderson Cancer Center, University of Texas at Houston - MD Anderson Cancer Center, University of Groningen, University of Groningen - Department of Radiation Oncology and University of Texas at Houston - MD Anderson Cancer Center
Downloads 14 (1,509,872)

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Dysphagia, normal tissue complication probability, Deep learning, Head and neck cancer, Risk prediction, radiotherapy, Radiation-induced toxicity