Summary
Artificial intelligence (AI) systems that read clinical notes and medical images promise earlier diagnoses, personalized treatments, and lower costs. However, these systems face critical challenges that threaten their reliability and ethical use. Data integrity problems, such as mistakes or tampering, can distort models and endanger patient care. In addition, patient data may be withdrawn due to revoked consent or legal obligations. There is no reliable way to see where a medical model's training data came from, whether that data was tampered with, or how to delete patient records effectively
