High-quality expert annotations enhance artificial intelligence model accuracy for osteosarcoma X-ray diagnosis.

ABSTRACT: Primary malignant bone tumors, such as osteosarcoma, significantly affect the pediatric and young adult populations, necessitating early diagnosis for effective treatment. This study developed a high-performance artificial intelligence (AI) model to detect osteosarcoma from X-ray images using highly accurate annotated data to improve diagnostic accuracy at initial consultations. Traditional models trained on unannotated data have shown limited success, with sensitivities of approximately 60%-70%. In contrast, our model used a data-centric approach with annotations from an experienced oncologist, achieving a sensitivity of 95.52%, specificity of 96.21%, and an area under the curve of 0.989. The model was trained using 468 X-ray images from 31 osteosarcoma cases and 378 normal knee images wi

SUBMITTER: Hasei J 

PROVIDER: S-EPMC11531945 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature