Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 9 of 9 for “"Applicability domain"”.
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Contributions to evaluation of machine learning models. Applicability domain of classification models
… using ML models for many purposes in different domains, the validation of such predictive models is currently required more formally. Traditionally, there are many studies related to model evaluation, robustness, reliability, and the quality of the data and the data-driven models. However, those …
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Contributions to evaluation of machine learning models. Applicability domain of classification models
… using ML models for many purposes in different domains, the validation of such predictive models is currently required more formally. Traditionally, there are many studies related to model evaluation, robustness, reliability, and the quality of the data and the data-driven models. However, those …
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Estimation of the acute toxicity and prediction of the metabolism site for organic molecules using GALAS methodology /
… feature the ability of the quantitative model Applicability Domain (AD) evaluation via the estimated prediction Reliability Indices (RI). I.e., the obtained models conform to one of the main requirements for the QSAR model acceptance as an alternative research method by the EU regulatory …
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Accurate Uncertainty Quantification and Explainable Artificial Intelligence in Machine Learning Models for Toxicological Risk Assessment
… a Bayesian neural network is correlated with the applicability domain of the model. Finally, in chapter four a Bayesian neural network is constructed using a large Ames mutagenicity dataset and evaluated on four different data splits based on source data, showing state of the art performance. …
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Methods to Improve Virtual Screening of Potential Drug Leads for Specific Pharmacodynamic and Toxicological Properties
… that were built from small data sets, a lack of applicability domain (AD), not being readily available for use, or not following the OECD QSAR validation guidelines. This thesis attempts to address these problems with the following strategies. First, the data augmentation approach using putative …
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Effect of formulation factors on the skin penetration of drugs
… solvent mixtures through the comparison of the applicability domain of the available dataset with a commonly used skin absorption dataset (in water). With the addition of new data, the resulting QSAR models were able to estimate skin absorption of permeants from a complex mixture of solvents …
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Using Cell Painting and Chemical Data for Small-molecule Bioactivity and Toxicity Prediction
… performance with dedicated in vitro assays. The applicability domain of machine learning models trained on structural fingerprints for the prediction of biological endpoints is often limited by the lack of diversity of chemical space of the training data. We developed similarity-based merger …
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Improved In Silico Methods for Target Deconvolution in Phenotypic Screens
… methods has been the ability to assess the applicability domain of the models, that is, when the assumptions made by a model are fulfilled and which input chemicals are reliably appropriate for the models. Hence, a major focus of this work was to explore methods for calibration of machine …
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Predictive Modelling of the Primary and Secondary Pharmacology of Compounds in Drug Discovery
… on the same bioactivity dataset for the bromodomain-containing proteins. Furthermore, we established the applicability domain of the model by employing conformal prediction, which was further used to aid the selection of compounds for prospective experimental testing in bromodomain assays. We …