Ken Sekiya
Papers
1
Total Citations
1
H-Index
1
About
Ken Sekiya is a rising researcher in the field of medical imaging and radiology, with a focused interest in predictive modeling for surgical outcomes. His most notable contribution is the development of the "Novel model of the region of interest modified Mayo Adhesive Probability score," a 2025 study that refines a widely used clinical tool for assessing perinephric fat adhesion prior to partial nephrectomy. By modifying the region of interest in the Mayo Adhesive Probability (MAP) score, Sekiya’s work aims to improve preoperative risk stratification, potentially reducing complications in kidney surgery. Though early in his career—with his top-cited paper currently holding 1 citation—this innovative approach signals a promising trajectory in urological imaging and quantitative radiology. Sekiya’s research bridges the gap between traditional scoring systems and more precise, patient-specific assessments, showcasing a talent for translating complex anatomical data into actionable clinical insights. As his work gains traction, it is poised to influence how surgeons plan for complex renal procedures, marking him as a researcher to watch in the evolving landscape of image-guided medicine.
Research Focus
Key Achievements
Top Papers
- 1