Abstract
This study explores the use of computer vision to detect and recognize ventilation objects, such as masks and tubes, and their positions on a patient’s face. We developed and compared two models for this task: You Only Look Once (YOLO) and a Transfer Learning (TL) model. This paper details the development process and performance evaluation of both approaches. The TL model demonstrated superior accuracy (98%) compared to the YOLO model (93%).
Clinical Relevance—This research is relevant to healthcare providers and researchers interested in applying computer vision in medicine, particularly for automated object detection in video streams or real-time monitoring.