Data protection and AI compliance in health research: a relevant resource for institutions and companies against algorithmic vulnerability

Abstract

Artificial intelligence (AI) is becoming integral to health research, with applications in diagnosis, prognosis, and imaging segmentation across several medical fields. However, integrating health, biometric, and genetic data into AI systems raises ethical, legal, and practical challenges, particularly concerning discrimination and bias. Studies highlight the presence of bias, hindering AI model development in healthcare. Compliance with current legislation (e.g., GDPR), international frameworks (e.g., ISO), and forthcoming European AI regulation is pivotal. This paper emphasizes integrating these requirements into public entities and private organizations to ensure fair AI development and utilization in the health sector.