Abstract
In this paper we describe a comparative classification of Pneumonia using Convolution Neural Network. The database used was the dataset Labeled Optical Coherence Tomography (OCT) and Chest X-Ray Images for Classification made available by (Kermany, 2018) with a total of 5863 images, with 2 classes: normal and pneumonia. To evaluate the generalization capacity of the models, cross-validation of k-fold was used. The classification models proved to be efficient compared to the work of (Kermany et al., 2018) which obtained 92.8 % and the present work had an average accuracy of 95.30 %.

Abstract
The lack of physical activity and poor nutrition triggers various diseases, among them is diabetes. In this context, several researches seek ways that can mitigate these diseases to provide a better quality of life for people. Therefore, the present work aims to analyze the possible inhibitors of the enzyme Dipeptidil Peptidase 4 that hypotheses will be stipulated for the creation of new drugs through molecular docking techniques, that is, a computational simulation of combinations of drugs of the family of gliptins with other antidiabetics (metformin, glyburide and cucurbitacin). Among the results, it was observed that the antidiabetic cucurbitacin combined with the gliptines obtained greater energy during the process.

Abstract
This paper aims to compare the compression of electro-oculographic signals, based on the (EOG) from MIT / BIH database, and the electromyographic signals, based on the (EMG) from MIT / BIH database, for that purpose, two compression techniques that can be used in electro-oculograms and electromyograms was approached, the two techniques mentioned above, were, the discrete cosine transform and Fast Walsh Hadamard Transform. For statistic the methods used was, the Mean squared error, mean absolute error, signal-to-noise ratio and peak signal-to-noise ratio as well, and for results, the techniques and they performance on each tested signal.

Abstract
This paper shows the advantage of using different sensors such the Microsoft Kinect and Myo Armband to acquire movement description of the plantarflexion and dorsiflexion of the foot with the help of the quaternions and the EMG Myo sensor. For the integration of these devices, it was chosen Python to develop the algorithm and create an interface to aid the signal acquisition. This integration, enabling an accurate motion description as well as a scale of EMG signal, allow the possibility of quantifying the treatment of the people with equinus foot.

Abstract
This article describes a comparison of two neural networks, the multilayer perceptron and Neural Network, for the detection and classification of pneumonia. The database used was the Chest-X-Ray data set provided by (Kermany et al., 2018) with a total of 5840 images, with two classes, normal and with pneumonia. to validate the models used, cross-validation of k-fold was used. The classification models were efficient, resulting in an average accuracy of 92.16% with the Multilayer Perceptron and 94.40% with the Convolution Neural Network.

Abstract
The techniques of image filtering have undergone an explosive growth in the last years to make new advances and challenges. This is due to the fact, among several other reasons, the increase of the volume of images coming from several sources. Digital images have been used for a variety of purposes, from the storage of souvenirs to accurate medical exams. However, Images may be corrupted due to several factors. The challenge of suppression or noise attenuation has led to the search for improved techniques in order to preserve important characteristics of the image, but, on the other hand, there is no solution available to completely solve the problem, boosting the production of the work proposed here. In this paper proposes a method for noise attenuation in computed tomography images using a hybrid genetic algorithm, the proposed method seeks to optimize the results in the space of solutions composed by a series of techniques of noise filtering. At the end the proposed method is compared statistically with two other competing methods and after the resulting filtered images are shown.