Comparison of Prognostic Performance Between a Machine Learning Model and Manually Measured Grey-White-Matter Ratio on Early Brain Computed Tomography After Out-of-Hospital Cardiac Arrest.
Inoue; Ono; Okazaki; Ichiba · 2026 · Cureus
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract (excerpt)
Objectives Early prediction of neurological outcomes in patients with out-of-hospital cardiac arrest (OHCA) is critical for guiding treatment decisions. Machine learning (ML) model and grey-white matter ratio (GWR), both derived from brain…
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Metadata source: PubMed · DOI 10.7759/cureus.109468