D. Bontempi

Krishnaswamy, D., Bontempi, D., Thiriveedhi, V. K., Punzo, D., Clunie, D., Bridge, C. P., Aerts, H. J. W. L., Kikinis, R., & Fedorov, A. (2024). Enrichment of lung cancer computed tomography collections with AI-derived annotations. Scientific data, 11(1), Article 25. https://doi.org/10.1038/s41597-023-02864-y

Kehayias, C. E., Yan, Y., Bontempi, D., Quirk, S., Bitterman, D. S., Bredfeldt, J. S., Aerts, H. J. W. L., Mak, R. H., & Guthier, C. V. (2024). Prospective deployment of an automated implementation solution for artificial intelligence translation to clinical radiation oncology. Frontiers in Oncology, 13, Article 1305511. https://doi.org/10.3389/fonc.2023.1305511

Pai, S., Bontempi, D., Hadzic, I., Prudente, V., Sokac, M., Chaunzwa, T. L., Bernatz, S., Hosny, A., Mak, R. H., Birkbak, N. J., & Aerts, H. J. W. L. (2024). Foundation model for cancer imaging biomarkers. Nature Machine Intelligence, 6(3), 354-367. https://doi.org/10.1038/s42256-024-00807-9

Fedorov, A., Longabaugh, W. J. R., Pot, D., Clunie, D. A., Pieper, S. D., Gibbs, D. L., Bridge, C., Herrmann, M. D., Homeyer, A., Lewis, R., Aerts, H. J. W. L., Krishnaswamy, D., Thiriveedhi, V. K., Ciausu, C., Schacherer, D. P., Bontempi, D., Pihl, T., Wagner, U., Farahani, K., ... Kikinis, R. (2023). National Cancer Institute Imaging Data Commons: Toward Transparency, Reproducibility, and Scalability in Imaging Artificial Intelligence. Radiographics, 43(12), Article e230180. https://doi.org/10.1148/rg.230180

Weiss, J., Raghu, V. K. K., Bontempi, D., Christiani, D. C. C., Mak, R. H. H., Lu, M. T. T., & Aerts, H. J. W. L. (2023). Deep learning to estimate lung disease mortality from chest radiographs. Nature Communications, 14(1), Article 2797. https://doi.org/10.1038/s41467-023-37758-5

Tohidinezhad, F., Bontempi, D., Zhang, Z., Dingemans, A. M., Aerts, J., Bootsma, G., Vansteenkiste, J., Hashemi, S., Smit, E., Gietema, H., Aerts, H. J. W. L., Dekker, A., Hendriks, L. E. L., Traverso, A., & De Ruysscher, D. (2023). Computed tomography-based radiomics for the differential diagnosis of pneumonitis in stage IV non-small cell lung cancer patients treated with immune checkpoint inhibitors. European Journal of Cancer, 183(1), 142-151. https://doi.org/10.1016/j.ejca.2023.01.027

Traverso, A., Tohidinezhad, F., Bontempi, D., Dekker, A., Hendriks, L., & De Ruysscher, D. (2022). A Combined Radiomic and Clinical Model for the Differential Diagnosis of Pneumonitis in Patients with NSCLC (Non-Small Cell Lung Cancer) Patients Receiving Immunotherapy (IO Therapy). Medical Physics, 49(6), E191-E191.