Titlebook: Deep Learning for Biomedical Data Analysis; Techniques, Approach Mourad Elloumi Book 2021 Springer Nature Switzerland AG 2021 Deep Learning

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Designing Maintainable Softwaremedical imaging has emerged as a grand success for medical diagnostics and analysis. So, medical image fusion has become a suitable subsidiary for medical experts. This chapter aims to focus on different aspects of image fusion techniques and their applications in the area of medical imaging. This c

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Designing Maintainable Softwarelysis of a much larger set of variables combined with sophisticated imaging and analytic techniques, the traditional paradigm of pathology based on visually descriptive microscopy can be complemented and substantially improved by digital pathology, utilizing screen-based visualization of digital tis

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https://doi.org/10.1007/978-3-031-34214-1to be a different disease. That means the genomic activities varies among these different diseases and the normal tissue as well. Thanks to the power of computing, . (DL) techniques have become feasible to integrate multi-omics data generated from the cells/tissue to study the outcomes of cancer as

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Rafael F?o de Moura,Luigi Carrommon diseases, the amount of available labeled data is often insufficient, and a variety of strategies are being explored to deal with inadequate, noisy and missing data. This chapter describes the benefits of using DL models with EMR data for research to improve provisioning of health care in prima

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Classification of Sequences with Deep Artificial Neural Networks: Representation and Architectural Ifficacy of (1) different DNA sequence representations and (2) several . (DL) architectures that process sequences for the solution of the related supervised classification problems. Although developed for specific classification tasks, we think that such architectures could be served as a suggestion

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