drs. D.H. (Hung) Chu

Data Scientist

Center for Information Technology

Telephone:

E-mail:

d.h.chu rug.nl

ORCID Research Portal

Publications

Deep learning NTCP model for late dysphagia after radiotherapy for head and neck cancer patients based on 3D dose, CT and segmentations

de Vette, S. P. M., Neh, H., van der Hoek, L., MacRae, D. C., Chu, H., Gawryszuk, A., Steenbakkers, R. J. H. M., van Ooijen, P. M. A., Fuller, C. D., Hutcheson, K. A., Langendijk, J. A., Sijtsema, N. M. & van Dijk, L. V., 20-Jun-2025, MedRxiv.

Research output: Working paper › Preprint › Academic

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

de Vette, S. P. M., van Rijn-Dekker, M. I., Van den Bosch, L., Keijzer, K., Neh, H., Chu, H., Li, Y., Frederiks, M. L., van der Laan, H. P., Heukelom, J., van Luijk, P., van der Schaaf, A., Steenbakkers, R. J. H. M., Sijtsema, N. M., Hutcheson, K. A., Fuller, C. D., Langendijk, J. A., Moreno, A. C. & van Dijk, L. V., Apr-2025, In: Oral Oncology. 163, 11 p., 107224.

Research output: Contribution to journal › Article › Academic › peer-review

Predicting pulmonary hemodynamics in pediatric pulmonary arterial hypertension using cardiac magnetic resonance imaging and machine learning: An exploratory pilot study

Chu, H., Ferreira, R. J., Lokhorst, C., Douwes, J. M., Haarman, M. G., Willems, T. P., Berger, R. M. F. & Ploegstra, M.-J., 14-Jun-2025, (E-pub ahead of print) In: International Journal Of Cardiovascular Imaging. 12 p.

Research output: Contribution to journal › Article › Academic › peer-review

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

Chu, H., de Vette, S. P. M., Neh, H., Sijtsema, N. M., Steenbakkers, R. J. H. M., Moreno, A., Langendijk, J. A., van Ooijen, P. M. A., Fuller, C. D. & van Dijk, L. V., 1-Jan-2025, In: International Journal of Radiation Oncology, Biology, Physics. 121, 1, p. 269-280 12 p.

Research output: Contribution to journal › Article › Academic › peer-review

Identifying future high healthcare utilization in patients with multimorbidity – development and internal validation of machine learning prediction models using electronic health record data

Weil, L. I., Zwerwer, L. R., Chu, H., Verhoeff, M., Jeurissen, P. P. T. & van Munster, B. C., May-2024, In: Health and Technology. 14, 3, p. 433-449 17 p.

Research output: Contribution to journal › Article › Academic › peer-review

Predicting late taste loss with deep learning NTCP model using 3D dose, CT and OAR segmentations

Neh, H., Rozema-de Vette, S., Chu, H., Sijtsema, N. M., van Ooijen, P., Langendijk, J. A. & van Dijk, L. V., 2024.

Research output: Contribution to conference › Poster › Academic

Towards the global integration of a comprehensive toxicity risk profile for HNC patients

Rozema-de Vette, S., van Rijn-Dekker, I., van den Bosch, L., Keijzer, K., Neh, H., Chu, H., Li, Y., Frederiks, M., van der Laan, H. P., Heukelom, J., van der Schaaf, A., Hutcheson, K. A., Steenbakkers, R., Sijtsema, N. M., Fuller, C. D., Langendijk, J. A., Moreno, A. C. & van Dijk, L. V., 5-May-2024.

Research output: Contribution to conference › Abstract › Academic

Clusters of medical specialties around patients with multimorbidity – employing fuzzy c-means clustering to explore multidisciplinary collaboration

Verhoeff, M., Weil, L. I., Chu, H., Vermeeren, Y., de Groot, J., Burgers, J. S., Jeurissen, P. P. T., Zwerwer, L. R. & van Munster, B. C., 2023, In: BMC Health Services Research. 23, 15 p., 975.

Research output: Contribution to journal › Article › Academic › peer-review

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, L. V., van Ooijen, P. M. A., Langendijk, J. A., Both, S. & Sijtsema, N. M., Oct-2023, In: Physics and imaging in radiation oncology. 28, 8 p., 100502.

Research output: Contribution to journal › Article › Academic › peer-review

Deep Learning and Radiomics Based PET/CT Image Feature Extraction from Auto Segmented Tumor Volumes for Recurrence-Free Survival Prediction in Oropharyngeal Cancer Patients

Ma, B., Li, Y., Chu, H., Tang, W., De la O Arévalo, L. R., Guo, J., van Ooijen, P., Both, S., Langendijk, J. A., van Dijk, L. V. & Sijtsema, N. M., 18-Mar-2023, Head and Neck Tumor Segmentation and Outcome Prediction - 3rd Challenge, HECKTOR 2022, Held in Conjunction with MICCAI 2022, Proceedings. Andrearczyk, V., Oreiller, V., Depeursinge, A. & Hatt, M. (eds.). Springer Science and Business Media Deutschland GmbH, p. 240-254 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13626 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

All (12) publications

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