No abstract

Breast cancer is one the main death causes for women worldwide, as 16% of the diagnosed malignant lesions worldwide are its consequence. In this sense, it is of paramount importance to diagnose these lesions in the earliest stage possible, in order to have the highest chances of survival. While there are several works that present selected topics in this area, none of them present a complete panorama, that is, from the image generation to its interpretation. This work presents a comprehensive state-of-the-art review of the image generation and processing techniques to detect Breast Cancer, where potential candidates for the image generation and processing are presented and discussed. Novel methodologies should consider the adroit integration of artificial intelligence-concepts and the categorical data to generate modern alternatives that can have the accuracy, precision and reliability expected to mitigate the misclassifications.

Children from out-of-home care are a vulnerable population that faces high stress and anxiety levels due to stressful experiences, such as being abused, being raped, and violence. This problem could have negative effects on their bio-psycho-social well-being if they are not provided with comprehensive psychological treatment. Numerous methods have been developed to help them relax, but there are no current approaches for assessing the relaxation level they reach. Based on this, a novel smart sensor that can evaluate the level of relaxation a child experiences is developed in this paper. It evaluates changes in thermal biomarkers (forehead, right and left cheek, chin, and maxillary) and heart rate (HR). Then, through a k-nearest neighbors (K-NN) intelligent classifier, four possible levels of relaxation can be obtained: no-relax, low-relax, relax, and very-relax. Additionally, an application (called i-CARE) for anxiety management, which is based on biofeedback diaphragmatic breathing, guided imagery, and video games, is evaluated. After testing the developed smart sensor, an 89.7% accuracy is obtained. The smart sensor used provides a reliable measurement of relaxation levels and the i-CARE application is effective for anxiety management, both of which are focused on children exposed to out-of-home care conditions.

No abstract

Trier Social Stress Test (TSST) is an experimental psychological test that induces changes in autonomic, endocrinological and immunological activity. Two measures used to evaluate the inflammatory activity induced by this test are the interleukin 6 (IL-6), a cytokine sensitive to changes in sympathetic nervous activity, and the mean arterial pressure (MAP), a measure sensitive to changes in autonomic activity. This study had two goals: first, the study examined whether TSST increases IL-6 and MAP levels; second, pre- and post-TSST IL-6 levels were compared for participants whose IL-6 levels increased or decreased due to the TSST. Saliva samples of IL-6 and MAP were taken from 42 participants clinically healthy, without psychiatric history, and data were analysed via quantile comparisons. The results showed that TSST did not lead to an increase in sympathetic activity as indexed by IL-6. Instead, TSST led to increases in MAP. Also, there were significant differences between the IL-6 distributions of people whose IL-6 levels changed from low to high (63%) and from high to low (37%) before and after the TSST. These findings suggest that the TSST will not have the same effect on all participants; that is, individual differences can be assessed using a biomarker to identify people with specialized psychological care needs.