Значения термина classify patients на английском

The Cutoff Finder program was used to classify patients by BED.

National Institutes of Health Stroke Scale score, and ambulatory status could correctly classify patients' DVT status.

Introduction: The Ability Index was developed to classify patients with congenital heart disease into four functional classes.

Measurements: A full ear, nose, and throat examination was conducted to classify patients into CST and non-CST groups.

For efficacy, response criteria of the European League Against Rheumatism were used to classify patients as responders or non-responders.

The DSP used Bayes' theorem on 38 anamnestic and clinical variables to classify patients into one of nine diagnoses.

The specialists were asked to classify patients according to the WHO classification scheme, rate their confidence, and state their treatment plans.

First, qualitative test results were found to correctly classify patients' gait patterns with an average success rate of 85%.

Clinical data were used to classify patients into the three standard GAS tertiles and to score patients according to the HI.

Machine learning classification using candidate biomarkers generated highly accurate and predictive models to classify patients into preclinical AD or control category.

A new understanding, including alternative parameters of diastolic function, seems to be necessary to classify patients with heart failure and preserved systolic function.

This tool can classify patients between those at high risk of cardiovascular mortality (high-risk group) and those of low risk (low-risk group).

After the patients in the criterion sample were classified by logistic regression analysis, the results were used to classify patients in the replication sample.

The profile differences were independent of severity of dementia and were sufficiently robust to classify patients as Alzheimer's disease or Huntington's disease with 84% accuracy.

The presented system is able to classify patients and controls (for early diagnosis) with a sensitivity of 88% and a specificity of 86%.

By using these patterns, we classified patients' pain based on timing and severity.