2020
DOI: 10.1007/s00204-020-02813-3
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Optimum concentration–response curve metrics for supervised selection of discriminative cellular phenotypic endpoints for chemical hazard assessment

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“…The input of this model was the cellular response at 500 µM interpolated from the fitted log-logistic dose-response curves. This metric was found to be more predictive than the potency metrics of the response curves [22]. Based on an unbiased analysis of 210 phenotypic features, 30 phenotypic features were identified to create a model with the highest balanced accuracy (defined as the average of specificity and sensitivity) for correctly classifying the 69 reference chemicals [13].…”
Section: Prediction Of Hepatocyte Toxicity In Humansmentioning
confidence: 99%
“…The input of this model was the cellular response at 500 µM interpolated from the fitted log-logistic dose-response curves. This metric was found to be more predictive than the potency metrics of the response curves [22]. Based on an unbiased analysis of 210 phenotypic features, 30 phenotypic features were identified to create a model with the highest balanced accuracy (defined as the average of specificity and sensitivity) for correctly classifying the 69 reference chemicals [13].…”
Section: Prediction Of Hepatocyte Toxicity In Humansmentioning
confidence: 99%