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October 18, 2022The Lancet Digital HealthOpen Access

Interpreting area under the receiver operating characteristic curve

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The aim is to clarify the interpretation of the area under the receiver operating characteristic curve (AUC) in classification models.
Theoretical analysis of AUC calculations
Comparison of AUC with sensitivity and specificity
Application in various contexts.
AUC value provides a single measure of overall accuracy of the model.
Higher AUC indicates better model performance in distinguishing between classes.

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Implication

Demonstrates how to interpret the area under the receiver operating characteristic curve, highlighting its significance in evaluating model performance.

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status: Published

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Hond et al. (2022) studied this question.

synapsesocial.com/papers/69d8397a8c03fbaff8bee36f https://doi.org/10.1016/s2589-7500(22)00188-1

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Implication

Demonstrates how to interpret the area under the receiver operating characteristic curve, highlighting its significance in evaluating model performance.

Abstract

status: Published

Interpreting area under the receiver operating characteristic curve

Key Points

No abstract yet

Implication

Abstract

Discussion

Cite This Study

Interpreting area under the receiver operating characteristic curve

Key Points

No abstract yet

Implication

Abstract

Discussion

Cite This Study

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