A Stacked Autoencoder Neural Network Algorithm for Breast Cancer Diagnosis With Magnetic Detection Electrical Impedance Tomography Abstract: Magnetic detection electrical impedance tomography (MDEIT) ...

Here, we propose a novel deep-learning-based algorithm, Moanna, that is trained to integrate multi-omics data for predicting breast cancer subtypes. Moanna’s architecture consists of a semi-supervised ...

Micro neural network with multi-dimensional layers, multi-shaped data, fully or locally meshing, conv2D, ... clustering model is build. an autoencoder with two hidden layer and K-means clustering ...

1 Introduction. Graph neural networks have developed rapidly in node representation learning and graph data mining in recent years. The reason why we focus on the study of graph neural networks is ...

An autoencoder was an unsupervised learning algorithm that trains a neural network to reconstruct its input and more capable of catching the intrinsic ... Lai L and Pei J (2018) Prediction of ...

Autoencoder neural networks: These unsupervised machine learning systems, sometimes referred to as Autoassociators, ingest unlabeled inputs, encodes data, and then decodes the data as it attempts ...

Autoencoder is a type of neural network where the output layer has the same dimensionality as the input layer. In simpler words, the number of output units in the output layer is equal to the number ...