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Titlebook: Innovations in Machine and Deep Learning; Case Studies and App Gilberto Rivera,Alejandro Rosete,Nelson Rangel-Val Book 2023 The Editor(s) (

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Analysis and Interpretation of Deep Convolutional Features Using Self-organizing Mapsls, and quality measures; (iii) it is possible to select features suitable for classification and to describe complexity and diversity in the classes and to extract additional information about the images in the training datasets. An application example considering chest X-ray images for the classif
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Predirol: Predicting Cholesterol Saturation Levels Using Big Data, Logistic Regression, and DissipatHowever, considering the quantity of cholesterol and blood molecules generated in 3D, which required high computing power, we opted for the 3Dmol.js library based on WebGL for rendering 3D graphics within any web browser. PREDIROL seeks to raise awareness about the care of cholesterol concentration
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Convolutional Neural Network-Based Cancer Detection Using Histopathologic Imagese training of the CNN network. Furthermore, we implement Cancer Detection by proposing a learning-based framework on the open-source Histopathologic Cancer Detection dataset. This dataset is available on Kaggle. The proposed framework uses CNN to detect cancer using advanced deep learning frameworks
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of dendritic cell-based therapies suggests the need for a deeper understanding of immunobiology of these key cells of the immune system as they develop within the complex tumor microenvironment. Reanalyzing and reexamining the accumulated data and concepts in the field, as done in this chapter and
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