Ensemble-imbalance-based classification for amyotrophic lateral sclerosis prognostic prediction: identifying short-survival patients at diagnosis.

Prognosticating Amyotrophic Lateral Sclerosis (ALS) presents a formidable challenge due to patients exhibiting different onset sites, progression rates, and survival times. In this study, we have developed and evaluated Machine Learning (ML) algorithms that integrate Ensemble and Imbalance Learning techniques to classify patients into Short and Non-Short survival groups based on data collected during diagnosis. We aimed to identify individuals at high risk of mortality within 24 months of symptom onset through analysis of patient data commonly encountered in daily clinical practice. Our Ensemble-Imbalance approach underwent evaluation employing six ML algorithms as base classifiers. Remarkably, our results outperformed those of individual algorithms, achieving a Balanced Accuracy of 88% and a Sensitivity of 96%. Additionally, we used the Shapley Additive Explanations framework to elucidate the decision-making process of the top-performing model, pinpointing the most important features and their correlations with the target prediction. Furthermore, we presented helpful tools to visualize and compare patient similarities, offering valuable insights. Confirming the obtained results, our approach could aid physicians in devising personalized treatment plans at the time of diagnosis or serve as an inclusion/exclusion criterion in clinical trials.

Analyzing a national health surveillance strategy to reduce mother-to-child transmission of syphilis: The case of Brazilian investigation committees.

Objectives: This study aimed to analyze the relevance of investigation committees in eliminating mother-to-child transmission of syphilis in Brazil. Methods: Questionnaires and interviews were conducted with health managers of 25 Brazilian Federative Units and Brazil's Federal District. Data were analyzed using Bardin's content analysis technique and subsequently compared with the global prescriptions for syphilis response of the Pan American Health Organization, World Health Organization, and recent research publications examining the course of syphilis in Brazil, in Brazilian regions, and globally. Results: While the investigation committees drew on the successful experience of those in reducing maternal mortality, which helped the country achieve the Millennium Development Goals, they are not demonstrated to be sufficient for preventing mother-to-child transmission of syphilis. The committees' systematic and bureaucratic agenda has not been efficient in managing avoidable factors for syphilis, nor do they operate in the scope of the integration of surveillance and care actions, as recommended by the health policy. Conclusion: The committees' model needs to be reviewed in the context of Brazil's National Health System. The research process should be rescaled in order to remain a cornerstone for the induction of health policy that integrates surveillance and healthcare across Brazilian Federative Units. The advancement toward an automated case management model becomes relevant for the country to meet global commitments to eliminate congenital syphilis transmission and achieve the goals outlined in the 2030 Agenda.

Effects of a self-care educational program via telerehabilitation on quality of life and caregiver burden in amyotrophic lateral sclerosis: a single-blinded randomized clinical trial protocol.

Introduction: The implementation of a telerehabilitation protocol for self-care in the routine of caregivers of individuals with amyotrophic lateral sclerosis (ALS) has been associated with reduced levels of stress and improved quality of life. Moreover, it may reduce the difficulty of traveling to perform physical or other self-care activities. Thus, this study designed a clinical trial protocol to investigate the effects of a self-care education program via telerehabilitation on the burden and quality of life of caregivers of individuals with ALS. Methods: This single-blinded randomized clinical trial will recruit 26 caregivers and randomly allocate them to the experimental (EG = 13) or control group (CG = 13). The EG will receive an informative booklet and participate in a 6-week synchronous telerehabilitation program with a neuropsychologist, nutritionist, and physiotherapist to discuss physical and mental health. The CG will receive an informative booklet on self-care and physical activity and weekly phone calls for 6 weeks to solve questions about the booklet. Outcomes will include the caregiver burden (Zarit scale), quality of life (World Health Organization Quality of Life BREF), pain (McGill Pain Questionnaire), stress (Perceived Stress Scale), and depression (Beck Depression Inventory), which will be evaluated at the baseline after the six-week program and 30 days after the program. Additionally, we will assess daily the nocturnal awakenings, sleep patterns, level of physical activity, and heart rate variability. Discussion: This study aimed to investigate the effectiveness of telerehabilitation for caregivers of individuals with ALS. If effective, this program could be disseminated among health professionals, increasing the possibility of remotely monitoring individuals with difficulty performing physical activities. Trial registration number: NCT05884034 (clinicaltrials.gov).

Data-driven computational intelligence applied to dengue outbreak forecasting: a case study at the scale of the city of Natal, RN-Brazil.

Dengue is recognized as a health problem that causes significant socioeconomic impacts throughout the world, affecting millions of people each year. A commonly used method for monitoring the dengue vector is to count the eggs that Aedes aegypti mosquitoes have laid in spatially distributed ovitraps. Given this approach, the present study uses a database collected from 397 ovitraps allocated across the city of Natal, RN-Brazil. The Egg Density Index for each neighborhood was computed weekly, over four complete years (from 2016 to 2019), and simultaneously analyzed with the dengue case incidence. Our results illustrate that the incidence of dengue is related to the socioeconomic level of the neighborhoods in the city of Natal. A deep learning algorithm was used to predict future dengue case incidence, either based on the previous weeks of dengue incidence or the number of eggs present in the ovitraps. The analysis reveals that ovitrap data allows earlier prediction (four to six weeks) compared to dengue incidence itself (one week). Therefore, the results validate that the quantification of Aedes aegypti eggs can be valuable for the early planning of public health interventions.

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.

Analyzing the reach of public health campaigns based on multidimensional aspects: the case of the syphilis epidemic in Brazil.

BACKGROUND: Public health campaigns aim to promote awareness, increase knowledge, and encourage a target population to adopt desirable attitudes and behaviors. Assessing their reach from a multidimensional perspective through information technology can facilitate the development of more effective campaigns in public health response. METHODS: We scrutinized seven data sources from different perspectives to assess a health campaign launched in Brazil named "Syphilis No!". This campaign is part of an Agenda for strategic actions to reduce syphilis in Brazil which includes dissemination of educommunication materials to remind people of the importance of syphilis prevention, emphasizing "test, treat and cure" concept. We developed a multidimensional analysis framework and implemented an information system to process the data from a time series perspective, and assessed the effects over time, both before and after the campaign. We descriptively analyzed data related to the campaign, including e-news, search engine activity, online courses, serological tests, medication distribution and case notification rates. FINDINGS: Regarding search engine activity, we observed the highest volume of search during the first week of campaigns in 2018 (between November 25th and December 7th). Nevertheless, analyzing this data in a trend plot revealed sustained growth until the end of 2019. From March 2018, the amount of e-news posts related to syphilis in Brazil, indexed by Google, followed an increasing slope, with a record peak in October 2019. In addition, data showed that 12 new online courses related to syphilis disease were available on the AVASUS Platform Learning Management System (LMS), to support efforts to promote lifelong learning for health professionals, teachers, and students. These courses reached more than 22,000 students between February 2019 and September 2020. Serological test data showed that the number of tests carried out in 2019 were 375·18% more than in 2015, even accounting for population growth. Finally, starting from the middle of 2018, the syphilis case notification rates followed a decreasing curve. INTERPRETATION: From this perspective, the "Syphilis No!" Project was a positive influence, inducing policy to fight syphilis in Brazil by supporting the implementation of a testing, treatment, and cure agenda (#TesteTrateCure). Certainly, this inference was made by analyzing multidimensional aspects and because, prior to 2018, the country had largely neglected this disease, with no records of communication actions during that period.