The use of complex classification algorithms such as deep learning techniques does not allow the researchers to identify the most discriminant features for tumor classification as they lack interpretability. This study aims to develop an algorithm capable of differentiating a set of dermoscopic images depending on whether the tumor is benign or malignant. The priority of this research is to obtain the importance of each extracted feature. This work is focused on the ABCD rule feature analysis and it aims to find the relevance of each feature and its performance in a classification model. A relevant aspect of this study is the use of a heterogeneous database, where the images were uploaded by different sources worldwide. A combination of novel and previously used features are analyzed and their importance is computed by the use of a Gaussian mixture model. After selecting the most discriminant features, a set of classification models was applied to find the best model with the less quantity of features. We found that a total of 65.89% of the features could be omitted with a loss in accuracy, sensibility and specificity equal or lower than 2%. While similar performance measures have been employed in other studies, most results are not comparable, as the databases used were more homogeneous. In the remaining studies, sensitivity values are comparable, with the main difference that the proposed model is interpretable.
Organizational behavior and organizational cognitive neuroscience are newly established interdisciplinary fields that use scientific techniques to answer questions about behaviors within organizations. Clarifying the more precise role of emotions and their regulation in forming a judgment in different managerial decision-making contexts, exploring how team members function synchronously, and the links between psychophysiological traits and how they relate to leadership, have been recurring subjects of interest. In this document, we present the psychophysiological response of eight senior project managers and eight junior project managers as they are faced with a challenging situation designed to assess some of the most relevant personal skills in project management: teamwork, management, problem, and conflicts resolution. Noninvasive electroencephalography (EEG), voice recording (VoR) and video recording (ViR) were performed during the application of an Assessment Center evaluation in addition to before and after heart rate (HR), blood pressure (BP) and pulse oximetry (SpO2) measurements. The results suggest that the voice frequency is related to the task that a subject performs. In this case, an activity that requires active discussion causes a person to talk at a higher pitch, which is the mean value of the fundamental frequency of the voice. In relation to the analysis of the voice depending on the project management expertise, no significant differences were found for calculated voice features. These results suggest that the voice features are not related with the project management expertise. On the other hand, the coefficient of variation of facial redness for junior project managers groups was higher than those of the senior manager groups. This indicates that even though facial readiness was not universally higher for the junior project manager, it is much more prevalent in those with the shorter project management expertise. With respect to the estimation of subject’s task engagement, measured through head movement cue analysis, it can be said that this method of engagement estimation proved to be in accordance with the expert psychology’s opinion. In concern with EEG, no statistically significant differences were found in frontal asymmetry value between the discussion stage and the presentation and ideation stage and between Senior and Junior managers in the discussion stage. Regarding the before and after heart rate (HR), blood pressure (BP) and pulse oximetry (SpO2) measurements, even though, in general all three variables had a discernible behavior (HR and BP increased while SpO2 decreased), no statistical relevant differences were found in the pre and pose measurements. However, it can be said that the Assessment Center evaluation induced a physiological response on the subjects since, at least one of three variables varied for each subject.
The comet assay is a commonly used technique in molecular and cell biology fields, for studies in which the DNA damage of a cell is measured. For instance, it is useful to analyze whenever a carcinogenic cell is affected by chemical agents, helping with oncology research. Traditionally, in order to evaluate the damage of a cell, an expert observes the morphology and the intensity (brightness) of the resulting comet. However, taking into account that a large number of images have to be analyzed, this task may demand a lot of time to be done manually. In recent years, the comet assay analysis has been implemented semi-automatically and automatically with the rise of new image processing algorithms. Although these new algorithms reduce the time invested in the image analysis, some problems in comet identification and accurate measure of their components need to be improved. This project aimed to develop an algorithm and an interface, named CometLab, for flexible automatic comet segmentation. Its performance was assessed with a set of images and compared against an open source, available software called OpenComet. It was found that only 1 of the 15 features that were extracted by both algorithms was not statistically correlated (head diameter), meaning that the designed application is suitable; therefore, this research helped to obtain information about the performance of CometLab in comparison to OpenComet, which serves as setpoint for future works in which it would be possible to decide which algorithm is better.
Movement intention (MI) is the mental state in which it is desired to make an action that implies movement. There are certain signals that are directly related with MI; mainly obtained in the primary motor cortex. These signals can be used in a brain-computer interface (BCI). BCIs have a wide variety of applications for the general population, classified in two groups: optimization of conventional neuromuscular performances and enhancement of conventional neuromuscular performances beyond normal capacities. The main goal of this project is to analyze if neural rhythm modulation enhancement could be achieved by practicing, through a BCI based on MI detection, which was designed in a previous study. A six-session experiment was made with eight healthy subjects. Each session was composed by two stages: a training stage and a testing stage, which allowed control of a videogame. The scores in the game were recorded and analyzed. Changes in alpha and beta bands were also analyzed in order to observe if attention could in fact be enhanced. The obtained results were partially satisfactory, as most subjects showed a clear improvement in performance at some point in the trials. As well, the alpha to beta wave ratio of all the tasks was analyzed to observe if there are changes as the experiment progresses. The results are promising, and a different protocol must be implemented to assess the impact of the BCI on the attention span, which can be analyzed with the alpha and beta waves.