Deep Learning Myocardial Ischemia Risk Trends in Suspected Cancer Patients

Supplementary Material 2 from a study by Ken Kurisu, published on figshare in April 2026. The dataset contains temporal trends in myocardial ischemia risk estimated from 12-lead electrocardiograms using deep learning models. It focuses on individuals undergoing health checkups where cancer was suspected.

Use Cases

• Analyze temporal trends in deep learning-estimated ischemia_risk scores for patient cohorts.
• Correlate electrocardiogram-derived risk features with suspected_cancer status during checkups.
• Validate deep learning model outputs for ischemia prediction against temporal patient data.
• Study risk progression patterns over time using serial electrocardiogram recordings.

Strengths

• Data is recent, last updated in April 2026.
• Published under a permissive CC-BY-4.0 license.

Limitations

• Dataset is very small at 490.9 KB, indicating limited scope or a sample.
• Supplementary nature suggests it may be incomplete without the primary manuscript.

Provenance

Source

figshare, authored by Ken Kurisu.

Collection Method

Deep learning analysis applied to 12-lead electrocardiogram recordings.

Time Range

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Freshness

Last updated on 2026-04-08.

Geography

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