Jan Borggrefe
Papers
1
Total Citations
44
H-Index
1
About
Jan Borggrefe’s research lies at the intersection of medical imaging, radiomics, and precision oncology, with a particular focus on improving outcomes for lung cancer patients. His most-cited work, a 2019 study on radiomic analysis of planning computed tomograms, demonstrated how quantitative imaging features can predict radiation-induced lung injury and overall survival in patients undergoing robotic stereotactic body radiation therapy. This contribution, cited 44 times, highlights his role in advancing non-invasive biomarkers that guide personalized treatment planning and toxicity management. Borggrefe’s broader impact is evident in his integration of machine learning with clinical radiology, enabling more accurate risk stratification and therapeutic decision-making. His work has been instrumental in bridging the gap between imaging data and actionable clinical insights, particularly in the context of stereotactic body radiation therapy. By leveraging radiomics to anticipate adverse effects, he has helped refine radiation protocols, potentially reducing complications while maintaining efficacy. Borggrefe’s research continues to influence the field of radiation oncology, offering a data-driven pathway toward safer, more individualized cancer care.
Research Focus
Key Achievements
Top Papers
- 1