There is an increasing interest in the use of Deep Learning (DL) based methods as a supporting analytical framework in oncology. However, most direct applications of DL will deliver models with limited transparency and explainability, which constrain the
The tourism sector has not been immune to this change and is a sector in which the use of data has transformed decision-making in tourism management. Tourism has been one of the sectors most affected by COVID-19, and this has accelerated this transformation. The raw material of this transfo...
Before sleep data can be used for modelling, it must be pre-processed. As discussed in the preceding sections, there is a growing trend towards the integration of sleep data from various sensors. As such, there is a preponderance of unstructured multi-modal time-series data with substantial no...
Before sleep data can be used for modelling, it must be pre-processed. As discussed in the preceding sections, there is a growing trend towards the integration of sleep data from various sensors. As such, there is a preponderance of unstructured multi-modal time-series data with substantial no...
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Therefore, we found that genome assembly choice can alter the fundamental structure of scRNAseq datasets, impacting the number of genes and cells available for downstream analysis. Figure 1. Genome assembly can alter the nFeatures and nCounts of a scRNaseq dataset, impacting the number of cells ...
When the data structure is much more complex, deeper architectures, such as SDAEs, are necessary. SDAEs stack several autoencoders by taking the hidden layer of the previous autoencoder as the input layer of the next autoencoder. SDAEs compress the data layer by layer in the encoders and...