Explainable Transfer Learning for Sharp Injury Detection

This study presents an explainable AI framework for identifying sharp injuries in medical images using transfer learning. By leveraging pretrained deep neural networks, the model enhances detection accuracy while providing interpretable insights into its predictions. The approach combines efficiency with transparency, making it suitable for clinical decision support systems. Nomination Link: https://forensicscientist.org/award-nomination/?ecategory=Awards&rcategory=Awardee Website: https://forensicscientist.org/ Social media: You tube: https://www.youtube.com/@forensicscientistawards Twitter: https://x.com/AwardForensic Instagram: https://www.instagram.com/forensicaward/ Pinterest: https://in.pinterest.com/forensicaward/