Kim Travis

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BACKGROUND Due to recent advances in data storage and sharing for further data processing in predictive toxicology, there is an increasing need for flexible data representations, secure and consistent data curation and automated data quality checking. Toxicity prediction involves multidisciplinary data. There are hundreds of collections of chemical,(More)
—There is a growing interest in applying computational intelligence in the predictive toxicology (PT) domain, where a large number of predictive models are becoming available. Evaluation of such models is therefore considered to be a crucial part of their development and potential use, especially for regulatory purposes. The current evaluation approaches(More)
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