A Deep Learning Approach for Predicting Multiple Sclerosis.

This paper proposes a deep learning model based on an artificial neural network with a single hidden layer for predicting the diagnosis of multiple sclerosis. The hidden layer includes a regularization term that prevents overfitting and reduces the model complexity. The purposed learning model achieved higher prediction accuracy and lower loss than four conventional machine learning techniques.

Differences in the Visual Performances of Patients with Strabismus, Amblyopia, and Healthy Controls.

Unlabelled: The aim of this paper is to use the new definition of amblyopia and to define the overall visual performance of healthy controls (HCs), patients with strabismus (PS), and patients with refractive amblyopia (PRA), based on the interaction of selected visual abilities.

Method: A total of 398 participants were divided in three groups: HCs, PRA, and PS. Variables such as visual acuity, refractive state, degree of stereopsis, phoria state, magnitude, and type of deviation were analyzed using parametric and non-parametric tests.

Digital Pregnancy Test Powered by an Air-Breathing Paper-Based Microfluidic Fuel Cell Stack Using Human Urine as Fuel.

The direct integration of paper-based microfluidic fuel cells (μFC's) toward creating autonomous lateral flow assays has attracted attention. Here, we show that an air-breathing paper-based μFC could be used as a power supply in pregnancy tests by oxidizing the human urine used for the diagnosis. We present an air-breathing paper-based μFC connected to a pregnancy test, and for the first time, as far as we know, it is powered by human urine without needing any external electrolyte.

Distortion Calculation Method Based on Image Processing for Automobile Lateral Mirrors.

The automobile lateral-view mirrors are the most important visual support for driver safety; therefore, it is important they have robust quality control. Typically, the distortion of a lateral-view mirror is measured using the JIS-D-5705 standard; however, this methodology requires an expert person to perform the measurements and calculations manually, which can induce measurement errors. In this work, a semi-automatic distortion calculation method based on image processing is presented.

Hyperconnected Openings Codified in a Max Tree Structure: An Application for Skull-Stripping in Brain MRI T1.

This article presents two procedures involving a maximal hyperconnected function and a hyperconnected lower leveling to segment the brain in a magnetic resonance imaging T1 weighted using new openings on a max-tree structure. The openings are hyperconnected and are viscous transformations. The first procedure considers finding the higher hyperconnected maximum by using an increasing criterion that plays a central role during segmentation.

Changes in the Brain Activity and Visual Performance of Patients with Strabismus and Amblyopia after a Compete Cycle of Light Therapy.

This research assesses the brain activity and visual performance at baseline and after light therapy (LTH), of seventeen patients with strabismus and amblyopia (SA), and eleven healthy controls (HCs) from Querétaro, México. Quantitative electroencephalogram analysis (qEEG) was used to record the brain activity, and clinical metrics such as the visual acuity, angle of deviation, phoria state, stereopsis, and visual fields determined the visual performance. Results showed a constant higher alpha-wave frequency for HCs.

Analysis of the potential impact of strabismus with and without amblyopia on visual-perceptual and visual-motor skills evaluated using TVPS-3 and VMI-6 tests.

Purpose: To investigate the potential impact of strabismus and amblyopia on visual-perceptual skills (VPS) and visual-motor skills (VMS) of patients according to the type of strabismus, visual acuity (VA), state of binocularity, and sex.

Methods: This observational, transverse, prospective study analyzed a sample of 146 children with strabismus (88 male and 58 female) aged 5-15 years from Querétaro, México. To determine the strabismus type, we considered the deviation direction, frequency, binocularity state, and associated and dissociated elements.

Morphological background detection and enhancement of images with poor lighting.

In this paper, some morphological transformations are used to detect the background in images characterized by poor lighting. Lately, contrast image enhancement has been carried out by the application of two operators based on the Weber's law notion. The first operator employs information from block analysis, while the second transformation utilizes the opening by reconstruction, which is employed to define the multibackground notion.