Publication list

Anees, A., Field, M., & Holloway, L. (2026). Development of federated learning neural networks with combined horizontal and vertical data partitioning. Applied Soft Computing, 192, 114734. https://doi.org/10.1016/j.asoc.2026.114734

Chlap, P., Al Mouiee, D., Finnegan, R. N., Cui, J., Chin, V., Deshpande, S., & Holloway, L. (2025). PyDicer: An open-source python library for conversion and analysis of radiotherapy DICOM data. SoftwareX, 29, Article 102010. https://doi.org/10.1016/j.softx.2024.102010

Anees, A., Field, M., & Holloway, L. (2024). A neural network-based vertical federated learning framework with server integration. Engineering Applications of Artificial Intelligence, 138, Article 109276. https://doi.org/10.1016/j.engappai.2024.109276

Alam, F. I., Field, M., Mouiee, D. A., Chlap, P., Delaney, G. P., Vinod, S., Kumar, S., Cui, J., Haidar, A., Chin, V., Sykes, J., Ashworth, S., Ahern, V., Stuart, K., Bailey, M., Gandhidasan, S., Selvaraj, J., Ramachandran, P., & Holloway, L. (2024). 2167: Streamlining Radiotherapy Structure Nomenclature: A Multimodal Feature Learning Approach. Radiotherapy and Oncology, 194, S4524–S4528. https://doi.org/10.1016/S0167-8140(24)02420-4

Field, M., Vinod, S., Delaney, G. P., Aherne, N., Bailey, M., Carolan, M., Dekker, A., Greenham, S., Hau, E., Lehmann, J., Ludbrook, J., Miller, A., Rezo, A., Selvaraj, J., Sykes, J., Thwaites, D., & Holloway, L. (2024). Federated Learning Survival Model and Potential Radiotherapy Decision Support Impact Assessment for Non–small Cell Lung Cancer Using Real-World Data. Clinical Oncology (Royal College of Radiologists (Great Britain)), 36(7), e197–e208. https://doi.org/10.1016/j.clon.2024.03.008

Aly, F., Rønn Hansen, C., Al Mouiee, D., Sundaresan, P., Haidar, A., Vinod, S., & Holloway, L. (2023). Outcome prediction models incorporating clinical variables for Head and Neck Squamous cell Carcinoma: a systematic review of methodological conduct and risk of bias. Radiotherapy and Oncology, 183, Article 109629. https://doi.org/10.1016/j.radonc.2023.109629

Chin, V., Finnegan, R. N., Chlap, P., Otton, J., Haidar, A., Holloway, L., Thwaites, D. I., Dowling, J., Delaney, G. P., & Vinod, S. K. (2023). Validation of a Fully Automated Hybrid Deep Learning Cardiac Substructure Segmentation Tool for Contouring and Dose Evaluation in Lung Cancer Radiotherapy. Clinical Oncology (Royal College of Radiologists (Great Britain)), 35(6), 370–381. https://doi.org/10.1016/j.clon.2023.03.005

Finnegan, R. N., Chin, V., Chlap, P., Haidar, A., Otton, J., Dowling, J., Thwaites, D. I., Vinod, S. K., Delaney, G. P., & Holloway, L. (2023). Open-source, fully-automated hybrid cardiac substructure segmentation: development and optimisation. Australasian Physical & Engineering Sciences in Medicine, 46(1), 377–393.https://doi.org/10.1007/s13246-023-01231-w

Haidar, A., Field, M., Batumalai, V., Cloak, K., Al Mouiee, D., Chlap, P., Huang, X., Chin, V., Aly, F., Carolan, M., Sykes, J., Vinod, S. K., Delaney, G. P., & Holloway, L. (2023). Standardising Breast Radiotherapy Structure Naming Conventions: A Machine Learning Approach. Cancers, 15(3), 564. https://doi.org/10.3390/cancers15030564

Rønn Hansen, C., Price, G., Field, M., Sarup, N., Zukauskaite, R., Johansen, J., Grau Eriksen, J., Aly, F., McPartlin, A., Holloway, L., Thwaites, D., & Brink, C. (2022). Larynx cancer survival model developed through open-source federated learning. Radiotherapy and Oncology, 176, 179–186. https://doi.org/10.1016/j.radonc.2022.09.023