How do machine learning models perform in the detection of depression, anxiety, and stress among undergraduate students? A systematic review.

Undergraduate students are often impacted by depression, anxiety, and stress. In this context, machine learning may support mental health assessment. Based on the following research question: "How do machine learning models perform in the detection of depression, anxiety, and stress among undergraduate students?", we aimed to evaluate the performance of these models.

A pilot study of a new app based on self-compassion for the prevention and promotion of mental health among Brazilian college students.

Introduction: Epidemiological data suggest substantial issues on the mental health of university students worldwide. Self-compassion is associated with lower rates of psychological distress and better positive mental health. Thus, we have developed a app-based intervention based on self-compassion principles targeting the prevention and promotion of mental health in college students.

A systematic literature review on educational recommender systems for teaching and learning: research trends, limitations and opportunities.

Unlabelled: Recommender systems have become one of the main tools for personalized content filtering in the educational domain. Those who support teaching and learning activities, particularly, have gained increasing attention in the past years. This growing interest has motivated the emergence of new approaches and models in the field, in spite of it, there is a gap in literature about the current trends on how recommendations have been produced, how recommenders have been evaluated as well as what are the research limitations and opportunities for advancement in the field.

Occupational Stress Monitoring Using Biomarkers and Smartwatches: A Systematic Review.

This article presents a systematic review of the literature concerning scientific publications on wrist wearables that can help to identify stress levels. The study is part of a research project aimed at modeling a stress surveillance system and providing coping recommendations. The investigation followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.

Neonatal Hearing Screening: protocols, obstacles and perspectives of speech therapists in Brazil - 10 years of Brazilian Federal Law 12,303/2010.

Purpose: This study aims to know the current scenario of speech audiology therapy activities at NHS in Brazil, identifying its obstacles and perspectives, as well as verifying the adequacy of national NHS Programs to the pre-established quality indicators.

Methods: Analytical observational study, carried out with speech therapists in the exercise of NHS in Brazil, between August 2018 and August 2019, through a structured online questionnaire. Descriptive and correlational analyzes of the data were performed using the SPSS version 22.

Computer-aided diagnosis of hepatocellular carcinoma fusing imaging and structured health data.

Introduction: Hepatocellular carcinoma is the prevalent primary liver cancer, a silent disease that killed 782,000 worldwide in 2018. Multimodal deep learning is the application of deep learning techniques, fusing more than one data modality as the model's input.

Purpose: A computer-aided diagnosis system for hepatocellular carcinoma developed with multimodal deep learning approaches could use multiple data modalities as recommended by clinical guidelines, and enhance the robustness and the value of the second-opinion given to physicians.

Model for quality analysis of neonatal hearing screening software: theory applied.

Background: It is necessary to ensure functional diagnosis and auditory rehabilitation as part of a continuous and inseparable follow-up process that begins with Neonatal Hearing Screening to achieve the expected outcome in children with hearing loss. Different software controls the data of this process, adopting different strategies and involving the technology for this. However, there is no specific model available in the literature for analyzing the quality of the software aimed at recording and monitoring data from Neonatal Hearing Screening.

[Feeding consequences of orphans after the mother's death: a study using text mining software].

The study aims to describe the consequences for future feeding of orphans under five years of age, following the mother's death, applying open-access text mining software packages. This was a crosscutting study of articles indexed in PubMed and BIREME on the themes of maternal death and orphan children. We selected ten open-access articles published from 2005 to 2015 in which only the title or abstract were read and which met the selection criteria.

Development and Application of a System Based on Artificial Intelligence for Transcatheter Aortic Prosthesis Selection.

Introduction: The interest in Expert systems has increased in the medical area. Some of them are employed even for diagnosis. With the variability of transcatheter prostheses, the most appropriate choice can be complex.

Distance Learning Course for Healthcare Professionals: Continuing Education in Tuberculosis.

Background: Continuing education of healthcare workers (HCWs) is an essential strategy for the control of tuberculosis (TB) transmission, enabling HCWs in early detection and appropriate treatment of TB cases.

Methods: We developed a distance learning (DL) course on TB for nurses. We conducted a quasi-experimental before and after study to evaluate the DL community at the participant's learning level.

Integrated system to automatize information collecting for the primary health care at home.

Data collected in a consistent manner is the basis for any decision making. This article presents a system that automates data collection by community-based health workers during their visits to the residences of users of the Brazilian Health Care System (Sistema Único de Saúde - SUS) The automated process will reduce the possibility of mistakes in the transcription of visit information and make information readily available to the Ministry of Health. Furthermore, the analysis of the information provided via this system can be useful in the implementation of health campaigns and in the control of outbreaks of epidemiological diseases.