Wenbin Shi
Papers
1
Total Citations
4
H-Index
1
About
Wenbin Shi is a researcher whose work sits at the intersection of surgical oncology, geriatric medicine, and artificial intelligence. His primary research focus is the application of machine learning to improve perioperative outcomes, particularly for elderly patients undergoing colorectal cancer surgery. Shi’s most notable contribution is the development of a risk factor prediction model for postoperative complications in this vulnerable population, a study that has already garnered 4 citations since its 2025 publication. This work is significant because it leverages advanced computational techniques to address a critical clinical challenge—accurately identifying which elderly patients are at highest risk for complications, thereby enabling more personalized and proactive care. By integrating machine learning with traditional clinical risk factors, Shi’s model offers a practical tool for surgeons to optimize treatment plans and reduce adverse outcomes. His research not only advances the field of predictive analytics in surgery but also highlights the growing role of AI in geriatric oncology. Wenbin Shi’s work stands as a promising step toward safer, data-driven surgical care for an aging population.
Research Focus
Key Achievements
Top Papers
- 1