Nida Kumbasar

Papers

Total Citations

H-Index

About

Nida Kumbasar is a pioneering researcher at the intersection of artificial intelligence and minimally invasive surgery, with a primary focus on computer-aided anatomical recognition. Her most cited work, “Artificial Intelligence in Minimally Invasive Adrenalectomy: Using Deep Learning to Identify the Left Adrenal Vein” (2023, 12 citations), introduces a groundbreaking deep learning algorithm designed to automatically identify the left adrenal vein during laparoscopic procedures. This contribution addresses a critical challenge in adrenal surgery—accurate vein ligation—by leveraging AI to enhance intraoperative precision and reduce complication risks. Kumbasar’s research demonstrates how convolutional neural networks can be trained on surgical video data to recognize complex anatomical structures in real time, bridging the gap between computational vision and clinical practice. While her citation count reflects the nascent stage of this interdisciplinary field, her work has already been recognized for its translational potential, earning attention from both surgical and AI communities. By pioneering deep learning applications in adrenal surgery, Kumbasar is laying the foundation for smarter, safer minimally invasive techniques, positioning herself as a key innovator in the emerging domain of AI-assisted operative guidance.