"Secure AI in Biomedical Imaging: Challenges and Solutions"

Abstract

The integration of artificial intelligence (AI) in biomedical imaging holds immense promise for advancing diagnostic accuracy and treatment efficacy. However, this intersection also presents significant challenges related to security and privacy. This paper explores the evolving landscape of secure AI in biomedical imaging, identifying key challenges such as data privacy, adversarial attacks, and regulatory compliance. It examines current solutions and methodologies aimed at mitigating these risks, including encryption techniques, robust AI model architectures, and secure data sharing frameworks. By analyzing these challenges and solutions, this paper contributes to a deeper understanding of the critical issues surrounding the deployment of AI in biomedical imaging and offers insights into safeguarding sensitive medical data while harnessing the transformative potential of AI technologies.