Ricardo Alexsandro de Medeiros Valentim

This systematic review examined the use of surface electromyography (sEMG) for the neuromuscular assessment of individuals with Amyotrophic Lateral Sclerosis (ALS), focusing on clinical parameters, the muscle groups evaluated, acquisition protocols, technical properties of the recording systems, integration with other technologies, and signal processing strategies. We included observational studies that applied sEMG to individuals diagnosed with ALS, with or without comparison to healthy controls, and without restrictions on publication year. The analyses included signals recorded at rest and during voluntary contractions, with or without the use of biofeedback. Most studies employed conventional or high-density surface electrodes, with sampling frequencies ranging from 500 Hz to 3000 Hz. The results showed that the primary parameters assessed were muscle fatigue, fasciculation patterns, the number of motor units (MUNE/MUNIX), motor unit firing rates, and signal complexity. These parameters demonstrated sensitivity to disease progression and may contribute to early diagnosis, phenotypic stratification, and functional monitoring of ALS. Additionally, the studies highlighted the increasing use of advanced computational approaches, such as machine learning, for feature extraction and automated classification. In conclusion, sEMG is a promising tool for functional assessment in ALS, with the potential to improve diagnostic accuracy and support new therapeutic strategies based on electrophysiological biomarkers. However, despite technological advances, the included studies displayed substantial methodological heterogeneity and limited protocol standardization. Integration with other neurophysiological modalities also remains underexplored, despite its significant clinical potential.

Background: The evaluation of health technologies is fundamental to the sustainability of the Brazilian National Health System (SUS), especially in highly complex and costly procedures such as computed tomography (CT). Objective: This study analyzed the financial efficiency of CT scanner use in the SUS in the state of Rio Grande do Norte (Brazil), considering the distribution of supply, the profile of providers, and the idle capacity of the public network. Methods: A total of 49,061 CT scan requests registered in the state system “RegulaRN Ambulatorial” between October 2023 and January 2025 were examined. Subsequently, data cleaning and grouping were performed. Results: The results indicated that 66.8% (24,769/37,089) of requests were from patients with cancer, 61.2% (22,703/37,089) were women, predominantly from municipalities with higher population densities, such as Natal and Mossoró, with an average waiting time of 44.86 (SD 88.43) days. More than 36,000 (99%) requests for the examinations were performed by private and philanthropic hospitals contracted by SUS, while public units with CT scanners accounted for less than 1% of production, evidencing significant underutilization. Conclusions: The findings suggest that strategically shifting demand to the public health system can increase efficiency, reduce costs and waiting times, and promote greater equity in access, contributing empirical evidence for more rational public policies on the use of diagnostic technologies.

As casas inteligentes representam uma importante evolução tecnológica no contexto da automação residencial, integrando recursos como Internet das Coisas (IoT), inteligência artificial, sensores inteligentes e sistemas automatizados voltados à otimização das atividades domésticas. O presente estudo teve como objetivo analisar as principais tecnologias aplicadas às smart homes, bem como seus benefícios, desafios e perspectivas. Trata-se de uma revisão integrativa da literatura, realizada por meio de buscas nas bases SciELO, Latindex, Springer, repositórios OJS e universitários, utilizando estudos publicados entre 2022 e 2026 nos idiomas português e inglês. Os resultados demonstraram que as casas inteligentes contribuem para a ampliar o conforto, segurança, da eficiência energética, praticidade e acessibilidade, beneficiando especialmente idosos, pessoas com limitações funcionais e indivíduos com Esclerose Lateral Amiotrófica (ELA). Também foram identificados desafios relacionados aos custos de implementação, interoperabilidade entre dispositivos, privacidade e segurança digital. Além disso, observou-se que o avanço da inteligência artificial e das tecnologias conectadas tende a tornar os ambientes residenciais cada vez mais autônomos, sustentáveis e personalizados. Conclui-se que as smart homes possuem elevado potencial de transformação dos ambientes domésticos contemporâneos.

Este estudo analisa a integração de estratégias de Saúde Digital na regulação assistencial do Sistema Único de Saúde (SUS), com ênfase no papel ordenador da Atenção Primária à Saúde (APS). Trata-se de uma revisão integrativa da literatura, de caráter exploratório, conduzida nas bases SciELO, PubMed e Biblioteca Virtual em Saúde (BVS), com uso de descritores MeSH/DeCS, operadores booleanos e critérios de elegibilidade. Os resultados indicam que a adoção de arquiteturas interoperáveis, como aquelas baseadas em padrões HL7 FHIR, e a implementação da Rede Nacional de Dados em Saúde (RNDS) promovem avanços na integração, transparência, rastreabilidade e eficiência da regulação assistencial. Evidências reportadas na literatura nacional, incluindo experiências no Rio Grande do Norte e em Manaus, demonstram impactos como a redução de 14,01 pontos percentuais (≈24,7% de redução relativa) no absenteísmo e melhorias na gestão de leitos. Adicionalmente, o uso de técnicas de Inteligência Artificial e Machine Learning apresenta acurácia de até 84,01% na predição de desfechos clínicos, contribuindo para a qualificação da tomada de decisão. Conclui-se que a Saúde Digital constitui vetor estratégico para a sustentabilidade do SUS, embora sua consolidação dependa da superação de desafios relacionados à governança de dados, inclusão digital e conformidade com a Lei Geral de Proteção de Dados (LGPD).

Este estudo analisa a integração de estratégias de Saúde Digital na regulação assistencial do Sistema Único de Saúde (SUS), com ênfase no papel ordenador da Atenção Primária à Saúde (APS). Trata-se de uma revisão integrativa da literatura, de caráter exploratório, conduzida nas bases SciELO, PubMed e Biblioteca Virtual em Saúde (BVS), com uso de descritores MeSH/DeCS, operadores booleanos e critérios de elegibilidade. Os resultados indicam que a adoção de arquiteturas interoperáveis, como aquelas baseadas em padrões HL7 FHIR, e a implementação da Rede Nacional de Dados em Saúde (RNDS) promovem avanços na integração, transparência, rastreabilidade e eficiência da regulação assistencial. Evidências reportadas na literatura nacional, incluindo experiências no Rio Grande do Norte e em Manaus, demonstram impactos como a redução de 14,01 pontos percentuais (≈24,7% de redução relativa) no absenteísmo e melhorias na gestão de leitos. Adicionalmente, o uso de técnicas de Inteligência Artificial e Machine Learning apresenta acurácia de até 84,01% na predição de desfechos clínicos, contribuindo para a qualificação da tomada de decisão. Conclui-se que a Saúde Digital constitui vetor estratégico para a sustentabilidade do SUS, embora sua consolidação dependa da superação de desafios relacionados à governança de dados, inclusão digital e conformidade com a Lei Geral de Proteção de Dados (LGPD).

Health economics has established itself as a strategic function in the Brazilian National Health System (SUS), contributing to greater equity, transparency, and efficiency in the allocation of public resources. This study analyzes the institutional trajectory of the Department of Health Economics and Development (DESID) of the Ministry of Health from 2003 to 2023, highlighting its key milestones, strategic axes, and persistent challenges. The research, from a historical–social perspective, was based on a documentary and content analysis of 126 official records available in the Virtual Health Library (VHL)–Health Economics section and in DESID’s institutional collection, covering the period from 1988 to 2024. The results show that the department’s activities were structured around three central axes: management tools, monitoring and evaluation, and transparency and equity. These were operationalized in seven dimensions: financing regulation; management tools development; technical standardization and decentralization; budgetary control and efficiency; economic and technological evaluation; information production; and accountability and social control. Over two decades, DESID has promoted systems such as the Public Health Budget Information System and the Health Price Bank, produced manuals, glossaries, and bulletins, and strengthened fiscal transparency and evidence-based decision-making. However, major gaps remain, including the absence of systematic impact assessments, weak economic regulation of the private sector, and limited focus on vulnerable populations. It is concluded that, despite advances in institutionalizing health economics as a strategic technical area in the SUS, there remains an urgent need for a national health economics policy to ensure equity, sustainability, and efficiency in public health financing in Brazil.

Context: The increasing digitalization of the healthcare sector generates massive volumes of heterogeneous data, a phenomenon known as Big Data, creating unprecedented opportunities to optimize processes such as the auditing of public accounts through Artificial Intelligence (AI). However, implementing effective AI systems requires a robust, scalable, and secure Big Data infrastructure, whose cost and complexity can be prohibitive. Objective: This article presents ALIAS (Architecture for Large-scale Intelligent Auditing of Healthcare Systems), a detailed and replicable technical blueprint for building a Big Data and AI platform. The goal is to provide a reference model based entirely on open-source technologies to democratize access to advanced analytics in the healthcare sector. Method: The architecture was developed and its feasibility investigated through a practical case study. The process included gathering requirements for healthcare auditing, selecting open-source technologies, and iterative implementation of the platform. Its effectiveness was evaluated through a real-world application. Results: The result is a complete blueprint implemented and tested at the Laboratory for Technological Innovation in Health (LAIS). The architecture comprises layers ranging from distributed storage and large-scale data processing to pipeline orchestration, data governance, and lifecycle management of AI models (MLOps). Its effectiveness is illustrated through a case study on intelligent classification of invoice items. Replicability is ensured through a public code repository with declarative manifests and lessons learned. Conclusion: ALIAS presents a robust and cost-effective solution for healthcare institutions to implement AI platforms, promoting technological sovereignty, transparency, and improved efficiency and quality of services.

Introduction: The interfaces between the fields of communication, education and health have been indicated by international institutions such as the WHO and the European Centre for Disease Prevention and Control. However, hegemonic scientific practices supersede dialogue between the three fields, isolating their practices. This fragmenting tendency is observed in scientific literature, which has created gaps in the dialogue and articulation between communication, education and health. Although health promotion requires both communicative and educational practices, the epistemological, historical, political, cultural and socioeconomic aspects have also engendered tensions between the fields. Communication is often seen as a mere instrument for other practices, rather than a phenomenon that (re)produces meanings and power dynamics. In opposing the reductionist and instrumentalising perspectives of knowledge fields, the primary objective of the scoping review is to map the scientific evidence on the interfaces between communication and education in health to indicate a conceptual framework that articulates communication and education practices within the context of health. Methods and analysis: A transdisciplinary team developed this protocol based on the 2024 Joanna Briggs Institute Manual for Evidence Synthesis. The procedures required to conduct the review were guided by the frameworks proposed by Arksey and O'Malley, Levac et al and Peters et al. The study eligibility criteria were established based on the Problem, Concept and Context outlined in the research questions. Primary and secondary studies will be retrieved from nine sources, covering both conventional and grey literature. These sources include Embase, ERIC, LILACS, PubMed/MEDLINE, ScienceDirect, Scopus, Web of Science, the Brazilian Digital Library of Theses and Dissertations, and the Networked Digital Library of Theses and Dissertations. A categorised form will be used for data collection and subsequent analysis. The reporting of the review findings will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews. Ethics and dissemination: The nature of the research and the use of secondary data sources do not require informed consent forms or approval from ethics committees in Brazil. The scientific findings from the review will be disseminated through peer-reviewed journals, academic conferences and other scientific communication channels. Study registration: The protocol was registered on the Open Science Framework (OSF) and is available at https://doi.org/10.17605/OSF.IO/Z3CX7 .

O presente estudo teve como objetivo analisar comparativamente dois Ambientes Virtuais de Aprendizagem (AVA) públicos brasileiros, o AVASUS, vinculado ao Ministério da Saúde, e o AVAMEC, vinculado ao Ministério da Educação, identificando suas potencialidades, limitações e contribuições para a Educação Mediada por Tecnologias. A pesquisa, de natureza qualitativa e caráter descritivo, foi desenvolvida entre maio e setembro de 2025, com base em análise documental e observação direta das plataformas. Foram examinados aspectos como estrutura pedagógica, usabilidade, acessibilidade, relevância temática e impacto social, considerando objetivos institucionais e perfil dos usuários de cada ambiente. Os resultados revelaram que o AVASUS se destaca pela sua efetividade pedagógica, coerência com políticas de formação em saúde e melhor relação custo-benefício por aluno certificado, enquanto o AVAMEC apresenta maior diversidade temática, amplitude de alcance e forte impacto social na formação docente. Ambos evidenciam avanços na democratização do conhecimento, mas enfrentam desafios relacionados à acessibilidade plena e à otimização da experiência móvel. Conclui-se que o fortalecimento dessas plataformas exige inovação contínua e políticas públicas articuladas, visando à consolidação de uma educação digital pública de qualidade, inclusiva e sustentável no Brasil.