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

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Snake Optimization of Multiclass SVM for Efficient Diagnosis of Heart Disease Risk Predictionnge due to its complexity and the need for both precision and efficiency. Early detection is pivotal in lowering the risk of fatality. Various factors such as age, gender, cholesterol and glucose levels, and heart rate contribute to the onset of severe cardiac issues. However, due to the multifacete
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Deep Artificial Neural Network Regression Model for Synergistic Drug Combination Predictionion can be challenging. Therefore, many computational methods proposed to predict drug interactions that can be used before clinical experiments and reduce the risk of adverse effects during treatment. in this paper, we proposed a deep artificial neural network regression (DANNR) model that can meas
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Classification of Benign and Malignant Breast Tumor Based on Machine Learning and Feature Selection roposed model consists of three main stages: data pre-processing, feature selection, and finally different classifiers. During the pre-processing phase, missing values are addressed and the data is normalised. Subsequently, three different techniques are employed to select the most crucial features:
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Artificial Intelligence in Finance Sector for Risk Prediction Data Analytics. AI has significantly impacted the financial industry by enhancing risk assessment, management, and decision-making. It can efficiently process vast amounts of data and identify patterns quickly. This paper presents an AI model in finance sector for risk management, especially loan d
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