Assessing the calibration in toxicological in vitro models with conformal prediction

Assessing the calibration in toxicological in vitro models with conformal prediction

Abstract Machine learning methods are widely used in drug discovery and toxicity prediction. While showing overall good performance in cross-validation studies, their predictive power (often) drops in cases where the query samples have drifted from the training data’s descriptor space. Thus, the ass...

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Bibliographic Details
Main Authors: Andrea Morger, Fredrik Svensson, Staffan Arvidsson McShane, Niharika Gauraha, Ulf Norinder, Ola Spjuth, Andrea Volkamer
Format: Article
Language:English
Published: BMC 2021-04-01
Series:Journal of Cheminformatics
Subjects:
Toxicity prediction
Conformal prediction
Data drifts
Applicability domain
Calibration plots
Tox21 datasets
Online Access:https://doi.org/10.1186/s13321-021-00511-5

Internet

https://doi.org/10.1186/s13321-021-00511-5

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