Artificial intelligence applied to analyzes during the pandemic: COVID-19 beds occupancy in the state of Rio Grande do Norte, Brazil.

The COVID-19 pandemic is already considered one of the biggest global health crises. In Rio Grande do Norte, a Brazilian state, the RegulaRN platform was the health information system used to regulate beds for patients with COVID-19. This article explored machine learning and deep learning techniques with RegulaRN data in order to identify the best models and parameters to predict the outcome of a hospitalized patient. A total of 25,366 bed regulations for COVID-19 patients were analyzed. The data analyzed comes from the RegulaRN Platform database from April 2020 to August 2022. From these data, the nine most pertinent characteristics were selected from the twenty available, and blank or inconclusive data were excluded. This was followed by the following steps: data pre-processing, database balancing, training, and test. The results showed better performance in terms of accuracy (84.01%), precision (79.57%), and F1-score (81.00%) for the Multilayer Perceptron model with Stochastic Gradient Descent optimizer. The best results for recall (84.67%), specificity (84.67%), and ROC-AUC (91.6%) were achieved by Root Mean Squared Propagation. This study compared different computational methods of machine and deep learning whose objective was to classify bed regulation data for patients with COVID-19 from the RegulaRN Platform. The results have made it possible to identify the best model to help health professionals during the process of regulating beds for patients with COVID-19. The scientific findings of this article demonstrate that the computational methods used applied through a digital health solution, can assist in the decision-making of medical regulators and government institutions in situations of public health crisis.

Situational analysis of syphilis cases taking place between 2015 and 2021 in the state of Rio Grande do Norte - Brazil / Análise situacional da sífilis entre os anos de 2015 e 2021 no estado do Rio Grande do Norte, Brasil

Introduction: Syphilis is a sexually transmitted infection that represents a severe public health problem worldwide and in Brazil it has not been different. The national compulsory notifications regarding syphilis cases are significantly increasing, and therefore, this fact alone justifies the study of such a relevant subject. Objective: This work presents a situational analysis of syphilis cases in the state of Rio Grande do Norte, Brazil, between 2015 and 2021, aiming primarily at assisting public healthcare authorities in decision-making processes to cope with the disease. Concomitantly, this research aims to build knowledge as well as to provide awareness to the population. Methods: This study analyzed data from compulsory notifications reports from 2015 to 2021, available in the database of the Brazilian Unified Health System's Informatics Department, in the Brazilian Information System of Notifiable Diseases and in the Brazilian Health Surveillance Secretariat. Results: In the state, 70% of patients with syphilis are aged 15 to 39 years. The rate of patients affected with acquired syphilis that have low education is 48%, and for pregnant women, this value rises to 77%. The declared mixed-race patients represent 48% of notifications for acquired syphilis, and for mixed-race pregnant women, this value increases to 60%. In congenital syphilis, 98% of compulsory notifications occurred for children aged up to 7 days of birth. Conclusion: Syphilis in Rio Grande do Norte is a public health problem that mainly affects the vulnerable population, predominantly the groups at risk with low education, mixed race, and young-adult people, being of paramount importance to combat the disease through population awareness, as well as through constant and adequate compulsory notification.

Introdução: A sífilis é uma infecção sexualmente transmissível que representa um grave problema de saúde pública para o mundo, bem como para o Brasil. As notificações compulsórias nacionais de casos de sífilis estão crescendo significativamente, portanto esse fato por si só justifica o estudo centrado nesta temática de primordial importância. Objetivo: Este trabalho apresenta uma análise situacional da sífilis entre os anos de 2015 e 2021 no estado do Rio Grande do Norte, visando principalmente auxiliar as autoridades públicas de saúde nos processos decisórios em resposta à sífilis, mas também construir conhecimento e embasar a conscientização da população. Métodos: Foram analisados dados das notificações de 2015 a 2021 disponíveis na base de dados do Sistema Único de Saúde, no Sistema de Informação de Agravos de Notificação e na Secretaria de Vigilância em Saúde. Resultados: No estado, mais de 70% dos pacientes afetados por sífilis têm entre 15 e 39 anos de idade. A taxa de pacientes com baixa escolaridade e que foram notificados com sífilis adquirida é de 48% e, para as gestantes, esse valor sobe para 77%. Pacientes declarados pardos representam 48% das notificações para sífilis adquirida e, para gestantes pardas, esse valor amplia-se para 60%. Na sífilis congênita, 98% das notificações ocorreram para crianças com idade de até sete dias de nascidos. Conclusão: A sífilis no Rio Grande do Norte é um problema de saúde pública que atinge principalmente a população vulnerável, com predominância dos grupos de baixa escolaridade, raça parda e jovens adultos, sendo de suma importância o combate à doença por meio da conscientização da população, como também a constante e adequada notificação compulsória.

The influence of antenna gain and beamwidth used in OSSEUS in the screening process for osteoporosis.

Applications on electromagnetic waves in the field of biotelemetry have increased in the latest years, being used to prevent, diagnose, and treatment of several diseases. In this context, biotelemetry allows minimally invasive monitoring of the physiologic, improving comfort and patient care and significantly reducing hospital costs. Aiming to assist the mineral bone density classification, through a radio frequency signal (RF), for a later diagnosis of osteoporosis, Osseus was proposed in 2018. This equipment is a combination of the application of techniques and concepts of several areas such as software, electrical, electronic, computational, and biomedical engineering, developed at a low cost, with easy access to the population, and non-invasive. However, when placed on evaluation, potential improvements were identified to increase the stability of Osseus operation. It is proposed the implementation of improvements in the antennas used by Osseus, aiming its miniaturization, improvement in the reception of the RF signal, and better stability of the equipment's operation. Then, two antennas were built, one of which was used as a project for the second, which is an array. The array showed significant improvements in the radiation parameters relevant to the application, being a candidate to replace the antennas currently in use at Osseus.