TSIUNAS: A Videogame for Preventing Gender-Based Violence.

Gender-based violence (GBV) is a public health problem worldwide. Nonetheless, in rural areas and low-income countries, the problem may be more difficult to eradicate because there are stereotypes that reinforce negative attitudes toward women, which increase the severity of the problem. This article presents the development of "Tsiunas," a videogame designed to increase GBV awareness.

Correction: Evaluating the impact of multivariate imputation by MICE in feature selection.

[This corrects the article DOI: 10.1371/journal.pone.

Evaluating the impact of multivariate imputation by MICE in feature selection.

Unlabelled: Handling missing values is a crucial step in preprocessing data in Machine Learning. Most available algorithms for analyzing datasets in the feature selection process and classification or estimation process analyze complete datasets. Consequently, in many cases, the strategy for dealing with missing values is to use only instances with full data or to replace missing values with a mean, mode, median, or a constant value.

Epileptic spikes detector in pediatric EEG based on matched filters and neural networks.

Unlabelled: The electroencephalogram (EEG) is a tool for diagnosing epilepsy; by analyzing it, neurologists can identify alterations in brain activity associated with epilepsy. However, this task is not always easy to perform because of the duration of the EEG or the subjectivity of the specialist in detecting alterations.

Aim: To propose the use of an epileptic spike detector based on a matched filter and a neural network for supporting the diagnosis of epilepsy through a tool capable of automatically detecting spikes in pediatric EEGs.

Towards a Selection Mechanism of Relevant Features for Automatic Epileptic Seizures Detection.

Background: Epilepsy diagnosis is frequently confirmed using electroencephalogram (EEG) along with clinical data. The main difficulty in the diagnosis is associated with the large amount of data generated by EEG, which must be analyzed by neurologists for identifying abnormalities. One of the main research challenges in this area is the identification of relevant EEG features that allow automatic detection of epileptic seizures, especially when a large number of EEG features are analyzed.