Titlebook: Breaking Barriers with Generative Intelligence. Using GI to Improve Human Education and Well-Being; First International Azza Basiouni,Clau

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Mikrobasierte Verfahren der Datenanalyse,tions where machine learning models predict mental health crises from patterns in user data. Additionally, AI‘s integration into physical health apps that track and analyse user activity and physiological data highlights its role in promoting healthier lifestyle choices and preventive healthcare pra

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https://doi.org/10.1007/978-3-322-85952-5 out the factors that define the use and adoption of generative AI and its effects on other social sustainability factors like education, diversity, and readiness. The study therefore assists in filling gaps within the literature on AI in education and is beneficial for students, policymakers, educa

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https://doi.org/10.1007/978-3-322-85952-5adaptability to online education. The model‘s performance was evaluated using accuracy, precision, recall, and F1-score metrics. The Random Forest model achieved an accuracy of 88.3%. It showed high precision and recall for the ‘High’ and ‘Moderate’ adaptability classes but lower performance in pred

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https://doi.org/10.1007/978-3-322-85952-5ayers with ReLU activation functions and dropout layers to prevent overfitting. The model is trained over 200 epochs with a batch size of 5, utilizing the Adam optimizer and categorical cross-entropy loss function. The results demonstrate the chatbot’s high accuracy and effectiveness, achieving an a

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