mlsanityData to 14 Oct 2026

CardioSyntax: end-to-end SYNTAX score prediction -- dataset, benchmark and method

arXiv 2407.19894 ↗First posted 29 Jul 2024cs.CV eess.IVcited by 3

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Abstract (arXiv)

The SYNTAX score has become a widely used measure of coronary disease severity, crucial in selecting the optimal mode of the revascularization procedure. This paper introduces a new medical regression and classification problem - automatically estimating SYNTAX score from coronary angiography. Our study presents a comprehensive CardioSYNTAX dataset of 3,018 patients for the SYNTAX score estimation and coronary dominance classification. The dataset features a balanced distribution of individuals with zero and non-zero scores. This dataset includes a first-of-its-kind, complete coronary angiography samples captured through a multi-view X-ray video, allowing one to observe coronary arteries from multiple perspectives. Furthermore, we present a novel, fully automatic end-to-end method for estimating the SYNTAX. For such a difficult task, we have achieved a solid coefficient of determination R2 of 0.51 in score value prediction and 77.3% accuracy for zero score classification.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 14 of its 51 references that are in the map. First posted on arXiv 29 Jul 2024.

Builds on

14 of 51 references.

References · 14

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2 more
  1. 2021A 3D CNN Network with BERT For Automatic COVID-19 Diagnosis From CT-Scan Imagescited by 6
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 3.

3 papers.

  1. 2026CARDIAG: A Dense Segment Classification Benchmark of Deep Learning Architectures for Coronary Angiographycited by 0
  2. 2026Modeling Clinical Workflow for SYNTAX Scoring from Coronary Angiography Videoscited by 0
  3. 2026SynSeq: End-to-End SYNTAX Score Prediction from Coronary Angiography Videoscited by 0