Abstract
Conference Title: 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER) Conference Start Date: 2019, March 20 Conference End Date: 2019, March 23 Conference Location: San Francisco, CA, USA Most of the regression-based Deep Learning (DL) algorithms which were recently proposed are based on Convolutional Neural Networks (CNN) trained by using l 2 loss function. In order to avoid the vulnerability of it to outliers, some authors propose to combine regression methods with a classification function like combination of l 2 loss function and softmax or a strategy based on bounding boxes what improves the performance of the DL neural network.In this research we propose using a combination of first order Stochastic Gradient Descent (SGD) optimizer for Artificial Neural Networks (ANNs) with Deep Learning (DL) and Deep Learning Multilayered Perceptron DLMLP with Back Propagation (BP). We focus on optimization of stochastic objectives, parameters and implementation of different activation functions in solving medical regression problems in high-dimensional space.