Medical AI Сan Diagnose. But Сan It Explain?

Medical AI can achieve high accuracy, but without interpretability, its predictions cannot be verified or trusted. In this article, I compare attention-based explanations and Integrated Gradients on a real clinical NLP task and show that not all explanation methods are equally reliable. The key takeaway: interpretability is not a model feature — it is what makes AI systems usable in practice.