Nickolas Papanikolaou
Papers
2
Total Citations
17
H-Index
2
About
Nickolas Papanikolaou is pioneering the integration of artificial intelligence and advanced imaging into urologic oncology, with a focus on improving outcomes for prostate cancer patients. His most-cited work introduces machine learning models for preoperative risk assessment of extracapsular extension (ECE) in men undergoing radical prostatectomy, demonstrating how predictive algorithms can refine surgical decision-making. By comparing decision curve analysis with traditional ROC metrics, he advances the clinical utility of AI beyond mere accuracy. In parallel, his feasibility study on diffusion tensor-based fiber tracking of the male urethral sphincter complex marks a significant step toward preserving urinary continence post-surgery. This work, with over a dozen combined citations, underscores his commitment to translating cutting-edge computational and imaging techniques into tangible patient benefits. Papanikolaou’s research sits at the intersection of data science and surgical precision, offering a roadmap for personalized risk stratification and functional preservation in prostate cancer care—a compelling model for the next generation of clinician-scientists.
Research Focus
Key Achievements
Top Papers
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