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arXiv Computer Vision By Christoph Baumann, Ronny Schweitzer, Noemi Pavo, Ulrike Attenberger, Christian Loewe, Philipp Seeb\"ock

SynSeq: End-to-End SYNTAX Score Prediction from Coronary Angiography Videos

Read the original on arXiv Computer Vision →

SynSeq is a video‑based method that directly predicts the SYNTAX score from coronary angiography videos, using targeted preprocessing and a zero‑inflation‑aware loss with linear target scaling. On the CardioSyntax dataset it outperforms prior state‑of‑the‑art approaches, improving $R^2$ by 0.55, reducing prediction bias by 93.1%, and delivering consistent performance across three expert graders. The model also achieves a weighted $F_1$‑score of 0.80 for revascularization treatment recommendations, approaching inter‑expert agreement.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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