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Multi-view Deep Learning Improves Detection of Major Cardiac Conditions from Echocardiography

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DataCite Commons2026-01-27 更新2026-05-03 收录
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https://www.openicpsr.org/openicpsr/project/241296/version/V2/view
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This dataset provides a minimal, fully de-identified example of the multiview echocardiography inputs used in “Multi-view Deep Learning Improves Detection of Major Cardiac Conditions from Echocardiography.” It contains 30 echocardiography studies, each with three standard non-Doppler views (apical four-chamber, apical two-chamber, and parasternal long-axis) along with a CSV file specifying file paths and study-level labels for ventricular abnormality. Videos were preprocessed exactly as described in the manuscript, including cropping to the echo cone, removing burned-in text, resizing to 224×224 pixels, and selecting the first 64 frames. This small dataset is intended only to illustrate the multiview data format and support reproducibility of model-loading and training code. It is not suitable for clinical modeling. All clips are fully de-identified and contain no protected health information.
提供机构:
ICPSR - Interuniversity Consortium for Political and Social Research
创建时间:
2026-01-27
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