Bone fracture are among the most common orthopedic injuries and pose a significant healthcare challenge due to their impact on patient mobility,quality of life,and recovery. Accurate and timely detection of fractures from radiography X-ray images is essential for effective diagnosis,treatment planning,and prevention of complications.However,many existing deep learning approaches focus primarily on imagelevel classification using conventional convolution neural networks (CNNS) and lack precise localization of fracture regions,which is critical for clinical interpretation.Moreover only a limited number of studies have explored unified object detection models capable of simultaneously localizing and identifying fractures within a single framework.To address these limitations,this study proposes a YOLOV8-based deep learning framework for automated bone fracture detection using publicly available radiographic Xray datasets.The dataset was annotated using Label Studio by marking fracture regions with bounding boxes to enable accurate object detection.The proposed model was trained with GPU acceleration to improve computational efficiency and support real-time inference.Performance was evaluated using standard metrics including precision,Recall,F1-Score,Accuracy and Mean Average Precision (mAP).Experimental results showed that the proposed YOLOV8 model achieved an overall detection accuracy of 72.3% demonstrating its capability for reliable fracture localization and automated detection.The developed system can be integrated into clinical decision support systems,radiology departments,hospitals,emergency care units,diagnostic imaging centres,and telemedicine platforms to support rapid fracture screening.it can also assist radiologists,orthropedic surgeons,emergency physicians,and healthcare professionals by providing an automated second opinion,reducing diagnostic time ,minimizing human error,improving clinical decision-making and ultimately enhancing patient care and treatment outcomes.

Mithrra B, Samasruthi S, Subasri N, Subhashree M, Ms Dhanya K R,"YOLOv8-Assisted Bone Fracture Detection Assessment from X-ray Images" International Journal of Advanced Multidisciplinary Research and Educational Development, V2(4): Page(425-428) July - August 2026. ISSN: 3107-6513. www.ijamred.com. Published by Scientific and Academic Research Publishing.