Titlebook: Advanced Communication and Intelligent Systems; Second International Rabindra Nath Shaw,Marcin Paprzycki,Ankush Ghosh Conference proceeding

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Louis M. Imbeau,Thomas C. Eboutous that are found in hospitals. Therefore, having a solid understanding of the data around heart disease is quite crucial if one wishes to increase the accuracy of their predictions. There have been a lot of experimental evaluations of the performance of models that have been developed using classifi

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Constitutional Convulsions in Modern Greeceiveness for the early diagnosis of the disease was shown by the system’s excellent precision as well as sensitivity in identifying pancreatic tumors. The outcomes of this investigation demonstrate the promise of AI-based systems for pancreatic cancer detection and diagnosis.

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Conclusion: Our Secrets Behind the Cloudeloped a Deep Neural Network (DNN) approach to tackle heterogeneous multi-social media data as a generic platform. This paper proposes a model for hate speech detection based on Deep Learning architecture. This model comprises multiple Deep neural networks combining Bidirectional-Long Short-Term Mem

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https://doi.org/10.1007/978-1-4614-0376-0ice, and trade rules. Rice types must traditionally be sorted by hand, which highlights the necessity for automated categorization using machine learning techniques..It is then demonstrated that the MobileNetV2 model, which was previously trained on the ImageNet dataset, can transfer learning to imp

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https://doi.org/10.1007/978-1-4614-0376-0a diverse and representative dataset of pneumonia images. Evaluation metrics such as accuracy, precision, recall, F1-score and area under the receiver operating characteristic curve (AUC-ROC) are employed. The key findings demonstrate that the combination of 2D wavelet transform and LBP-based featur