@inproceedings{46d79cbb95a0492d9ee2b02b74b1c12a,
title = "Classification of Surgeons' Gender from Videos of the Surgical Field",
abstract = "We present a novel approach to classify the gender of the operating surgeon in videos from the microscope (that show only the surgical field) using the SurgGender model and a step-based analysis technique. This method addresses both technical and ethical challenges of implicit gender biases, which impact training and career progression. By focusing on gender classification, our work aims to support equitable, context-aware surgical systems. The SurgGender leverages 3D shifted window-based self-attention to capture key spatialtemporal patterns. Our step-based approach enhances classification by isolating relevant video segments and reducing non-informative noise. Rigorous testing demonstrates that this method improves accuracy and processing efficiency, establishing a foundation for bias-aware surgical video analysis.",
keywords = "Cataract surgery, Gender Classification, Transformer",
author = "Shah, \{Nisarg A.\} and Ali, \{Ibrahim D.\} and Rishabh Nanawati and Abdulla Shaheen and Irene Catterson and Patel, \{Vishal M.\} and Vedula, \{S. Swaroop\} and Shameema Sikder",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 22nd IEEE International Symposium on Biomedical Imaging, ISBI 2025 ; Conference date: 14-04-2025 Through 17-04-2025",
year = "2025",
doi = "10.1109/ISBI60581.2025.10981110",
language = "English (US)",
series = "Proceedings - International Symposium on Biomedical Imaging",
publisher = "IEEE Computer Society",
booktitle = "ISBI 2025 - 2025 IEEE 22nd International Symposium on Biomedical Imaging, Proceedings",
}