Millie Summary:  High model accuracy doesn’t guarantee reliable performance. MedTech AI can learn misleading patterns from training data rather than the clinical characteristics it’s intended to recognize. Reliable AI depends on accurately connecting medical images, measurements, and device data while preserving the context and timing needed for meaningful predictions. AI performance must be continuously validated and monitored as real-world conditions change, with traceable data pipelines and controlled updates supporting long-term reliability and regulatory compliance Written by Ava Iannessa, Growth Development Analyst Could your model’s high-test accuracy be hiding its failure to recognize the abnormality it was trained to detect?  A medtech AI model can achieve high test accuracy by recognizing a scanner’s image characteristics instead of the anatomy or abnormality it was trained to...Read More