Predictive Accuracy of Admission Lab Tests for Severe COVID-19

A dataset evaluating the predictive accuracy of initial laboratory tests for severe COVID-19 outcomes. The dataset is 5.5 KB in size, authored by Ieva Kubiliute, and was last updated on 2026-05-29. It is available under a CC-BY-4.0 license.

Use Cases

• Build predictive models for severe COVID-19 based on admission laboratory test results.
• Evaluate the relative importance of different lab markers for forecasting patient deterioration.
• Benchmark the performance of simple clinical models against more complex algorithms.

Strengths

• Dataset is small (5.5 KB), facilitating quick download and inspection.
• Explicitly licensed under the permissive CC-BY-4.0 license for reuse.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare

Freshness

Last updated 2026-05-29 17:29:08; freshness should be verified.