APA (7th ed.) Citation

Louis, T., Lucia, F., Cousin, F., Mievis, C., Jansen, N., Duysinx, B., . . . Hustinx, R. (2024). Identification of CT radiomic features robust to acquisition and segmentation variations for improved prediction of radiotherapy-treated lung cancer patient recurrence. Scientific Reports, 14(1), 1. https://doi.org/10.1038/s41598-024-58551-4

Chicago Style (17th ed.) Citation

Louis, Thomas, et al. "Identification of CT Radiomic Features Robust to Acquisition and Segmentation Variations for Improved Prediction of Radiotherapy-treated Lung Cancer Patient Recurrence." Scientific Reports 14, no. 1 (2024): 1. https://doi.org/10.1038/s41598-024-58551-4.

MLA (9th ed.) Citation

Louis, Thomas, et al. "Identification of CT Radiomic Features Robust to Acquisition and Segmentation Variations for Improved Prediction of Radiotherapy-treated Lung Cancer Patient Recurrence." Scientific Reports, vol. 14, no. 1, 2024, p. 1, https://doi.org/10.1038/s41598-024-58551-4.