YOLOatt-Med: YOLO-Based Attention Mechanism for Medical Image Classification

Early and accurate diagnosis of respiratory diseases can significantly reduce mortality rates. This study presents a novel approach for classifying respiratory diseases from medical images using computer vision. The approach combines the YOLOv8 object detection model with CBAM to boost feature extraction and enhance classification precision. The effectiveness of the method was tested on two datasets: chest computed tomography scans for lung cancer detection and chest X-rays for pneumonia diagnosis. Results indicate that the CBAM-YOLOv8 model surpasses current leading methods, underscoring the method's efficiency in emphasizing essential image features for precise disease classification.