Exciting advancements are unfolding at the intersection of AI and radiation oncology. Here's a quick roundup of five papers from Intelligent Oncology that showcase how AI is reshaping radiotherapy planning, delivery, and personalized care.
1. Deep Learning for Motion Management in Radiotherapy
https://doi.org/10.1016/j.intonc.2025.06.006
Yang B, Wei R, Dai J. Deep learning applications in motion management for radiotherapy. Intelligent Oncology. 2025;1(3):244-255. doi:10.1016/j.intonc.2025.06.006
2. Benchmarking Deep Learning Frameworks for Abdominal Organ Auto-Segmentation
https://doi.org/10.1016/j.intonc.2025.03.003
Ram US, Pogue JA, Soike M, Pfister NT, Jacob R, Cardenas CE. Assessing quantitative performance and expert review of multiple deep learning-based frameworks for computed tomography-based abdominal organ auto-segmentation. Intelligent Oncology. 2025;1(2):160-171. doi:10.1016/j.intonc.2025.03.003
3. AI Delineation of Thoracic OARs on Multi-Institutional Datasets
https://doi.org/10.1016/j.intonc.2024.12.001
Ye X, Guo D, Zhao L, et al. Development and Validation of AI Delineation of the Thoracic RTOG Organs at Risk with Deep Learning on Multi-institutional Datasets. Intelligent Oncology. 2025;1(1):61-71. doi:10.1016/j.intonc.2024.12.001
4. Big Data and AI for Nasopharyngeal Carcinoma
https://doi.org/10.1016/j.intonc.2024.09.001
Zhen Z, Yang Y, Feng C, Lin L, Ma J, Sun Y. From Data to Decisions: Big Data and AI are Shaping the Future of Radiotherapy and Individualized Treatment of Nasopharyngeal Carcinoma. Intelligent Oncology. 2025;1(1):52-60. doi:10.1016/j.intonc.2024.09.001
5. Physics-Informed Diffusion Model for CyberKnife Dose Prediction
https://doi.org/10.1016/j.intonc.2026.100067
Li M, Xu H, Zhang X, et al. Monte Carlo–consistent dose prediction for clinical CyberKnife radiotherapy using a physics- and spatially-informed diffusion model. Intelligent Oncology. 2026;2(3):100067. doi:10.1016/j.intonc.2026.100067
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