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README.md

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 The dataset containes invasive coronary angiograms for the coronary dominance classification task, an essential aspect in assessing the severity of coronary artery disease.
 The dataset holds 1,574 studies, including X-ray multi-view videos from two different interventional angiography systems.
 Each study has the following tags: bad quality, artifact, high uncertainty, and occlusion. Those tags help to classify dominance classification more accurately and allow to utilize the dataset for uncertainty estimation and outlier detection.
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+More information about coronary dominance classification using neural networks in https://doi.org/10.48550/arXiv.2309.06958.
+Some angiographic studies from the dataset are from CardioSYNTAX dataset of coronary agiograms for the SYNTAX score prediction in https://doi.org/10.48550/arXiv.2407.19894
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