Researchers trained two identical residual networks on single‑heartbeat ECG images. One network received a pseudo‑colour encoding that fills the area under the QT interval with colours chosen from the QT‑nomogram, a clinical risk tool. The colour‑only model reached AUC scores of 0.903 and 0.914 on two UK‑Biobank visits, while the monochrome model stayed around 0.72. Across eight explanation techniques, the coloured inputs gave clearer and more stable localisation of the risky QT region.
Why it matters
Clinicians could rely on AI‑generated ECG explanations that align with known electrophysiology, improving trust in automated risk assessments.
