Publications by authors named "Chuanyu Fang"
Article Synopsis
- Bronchoscopy is crucial for diagnosing respiratory issues, but visualizing bronchial tubes is often difficult due to interference from substances like mucus and blood.
- This study explores enhancing object detection in bronchoscopy images using a YOLO algorithm integrated with a CBAM attention mechanism, aiming to improve accuracy for medical professionals.
- Results showed the YOLO-V8 model achieved an improved mean Average Precision (mAP) from 87.09% to 88.27% after integrating the attention module, demonstrating the effectiveness of this approach in medical imaging.
This study was dedicated to introducing a new method for predicting the Sauter mean diameter (SMD) buildup in the swirl cup airblast fuel injector. There have been considerable difficulties with predicting SMD mainly because of complicated flow characteristics in a spray. Therefore, the backpropagation (BP) neural network-based machine learning was applied for the prediction of SMD as a function of geometry, condition parameters, and axial distance such as primary swirl number, secondary swirl number, venturi angle, mass flow rate of fuel, and relative air pressure.
View Article and Find Full Text PDFBackground: Surgical masks (SMs) protect medical staff and reduce surgical site infections. Extended SM use may reduce oxygen concentrations in circulation, causing hypoxia, headache, and fatigue. However, no research has examined the effects of wearing SMs on oxygenation and physical discomfort of anesthesiologists.
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