This BSI white paper explores the use of machine learning (ML) and artificial intelligence (AI) in medical devices, addressing their potential and regulatory challenges. It defines key concepts like locked vs. adaptive algorithms and supervised vs. unsupervised learning. The paper emphasizes transparency, risk management, and explainability throughout the product lifecycle. Regulatory frameworks such as the EU MDR, IVDR, and FDA’s proposed regulations are discussed. BSI advocates a risk-based, evidence-led approach, stressing the need for clinical evaluation, bias monitoring, cybersecurity, and post-market surveillance to ensure safety and ethical use of AI in healthcare.

Join for free to read