Computational Toxicology Through Neural Network Architectures: Predictive Modelling of Pharmacological Adverse Effects
Keywords:
computational toxicology, neural network architectures, predictive modelling, pharmacological adverse effects, machine learningAbstract
Identifying the potential toxicological effects of a new drug has assumed a key role in pharmaceutical development trials. New tools based on artificial intelligence that can more effectively and accurately identify such effects are highly desirable. A first step in this direction is represented by machine learning-based approaches that predict if and to what degree a given compound may increase the risk for side effects.Downloads
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