Selection of 51 predictors from 13,782 candidate multimodal features using machine learning improves coronary artery disease prediction

Research article (Patterns, 2021) · cited 43× · AI/ML
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Selection of 51 predictors from 13,782 candidate multimodal features using machine learning improves coronary artery disease prediction

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Selection of 51 predictors from 13,782 candidate multimodal features using machine learning improves coronary artery disease prediction is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Selection of 51 predictors from 13,782 candidate multimodal features using machine learning improves coronary artery disease prediction. Retrieved May 24, 2026, from https://4ort.xyz/entity/selection-of-51-predictors-from-13-782-candidate-multimodal-features-using-machine-learning-improves-coronary-artery-dis
MLA “Selection of 51 predictors from 13,782 candidate multimodal features using machine learning improves coronary artery disease prediction.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/selection-of-51-predictors-from-13-782-candidate-multimodal-features-using-machine-learning-improves-coronary-artery-dis.
BibTeX @misc{4ortxyz_selection-of-51-predictors-from-13-782-candidate-multimodal-features-using-machine-learning-improves-coronary-artery-dis_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Selection of 51 predictors from 13,782 candidate multimodal features using machine learning improves coronary artery disease prediction}}, year = {2026}, url = {https://4ort.xyz/entity/selection-of-51-predictors-from-13-782-candidate-multimodal-features-using-machine-learning-improves-coronary-artery-dis}, note = {Accessed: 2026-05-24}}
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