Titlebook: Artificial Intelligence for Environmental Sustainability and Green Initiatives; Aboul Ella Hassanien,Ashraf Darwish,Sally M. Elgha Book 20

FER

Snake Optimization of Multiclass SVM for Efficient Diagnosis of Heart Disease Risk PredictionLinear function depends on optimal parameter selection; of kernel scale (gamma) (σ) and box constraint (C). Intelligent optimization methods such as Snake optimization are used to select the optimal values of kernel scale (σ) and box constraint (C). Compared to existing state-of-the-art models, our

Anecdote

Efficient Prediction Adverse Drug-Drug Interactions with Deep Neural Networks drug A is combined with drug B. After evaluating the models‘ performance. This paper suggested DNN as a way to enhance DDIs‘ predictive capabilities. The prediction algorithm was 96.2% accurate in predicting 86 different kinds of DDIs using a benchmark dataset. The proposed model applies pre-proces

ensemble

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Enhancing Synergistic Drug Combination Model Through Dimension Reduction in Cancer Cell Lines the application of entropy and Gini-based methods to further refine gene expression. Additionally, Gaussian feature selection is applied to pinpoint the 1,000 most significant genes. Autoencoders and variational autoencoders are also applied to reduce the dimensionality of gene expression data. Fur