Rosa Maria Grangeiro Martins,Dailon de Araújo Alves,Sabrina Alaide Amorim Alves et al.
Rosa Maria Grangeiro Martins et al.
The objective was to develop, validate, and test the usability of a chatbot as a support tool for healthcare professionals in the management of leprosy lesions. This methodological study involved content and appearance validation conducted ...
Artificial Intelligence with Convolutional Neural Networks for Microfilariae Detection in the Brazilian Amazon [0.03%]
基于卷积神经网络的人工智能在巴西亚马逊地区微丝状虫检测中的应用
João Carlos Silva de Oliveira,Patrícia Moura Sousa,Uziel Ferreira Suwa et al.
João Carlos Silva de Oliveira et al.
The Amazon region faces persistent structural limitations for the diagnosis of filarial diseases. This study aimed to develop and evaluate an artificial intelligence model based on convolutional neural networks to classify microscopic image...
Adherence of Artificial Intelligence Models to Brazilian guidelines for obesity in Primary Health Care [0.03%]
人工智能模型遵守巴西初级保健肥胖指南的程度
Felipe da Fonseca Silva Couto,Carlos Podalirio Borges de Almeida
Felipe da Fonseca Silva Couto
Obesity represents a growing challenge for Primary Health Care (PHC), demanding the use of new technologies and innovative solutions. This study evaluated the adherence of Large Language Models (LLMs) to Brazilian guidelines for obesity man...
Equity as a guiding principle of digital transformation: a model for resource allocation in the SUS Digital Program [0.03%]
包容与公平：巴西SUS数字计划资源分配模型指导原则研究报告摘要
Paulo Eduardo Guedes Sellera,Ana Estela Haddad,Inês Eugênia Ribeiro da Costa et al.
Paulo Eduardo Guedes Sellera et al.
This article presents the foundations, methodology, and territorial analyses that underpinned the creation of the Index of Criteria for the Distribution of Financial Resources for the Digital SUS Program (ICSD), developed by the Department ...
Digital Health coordinated by an enhanced Primary Health Care (PHC) System [0.03%]
由加强型初级卫生保健(PHC)系统协调的数字健康
Luiz Felipe Pinto,Luiz Alexandre Chisini,Zulmira Hartz et al.
Luiz Felipe Pinto et al.
Ana Luiza Ferreira Rodrigues Caldas
Ana Luiza Ferreira Rodrigues Caldas
Inequalities and regional planning: situational diagnosis of the SUS Digital Program [0.03%]
不平等与区域规划：SUS数字计划的现状诊断
Paulo Eduardo Guedes Sellera,Ana Estela Haddad,Alessandra Dahmer et al.
Paulo Eduardo Guedes Sellera et al.
This article presents the theoretical foundations, methodological approach, and key findings of the situational diagnosis conducted by the Department of Information and Digital Health, part of the Ministry of Health, covering the country's ...
Digital health ecosystem in the municipality of Rio de Janeiro, Brazil: the experience of the creation of the minhasaude.rio application [0.03%]
巴西里约热内卢市的数字健康生态系统：minhasaude.rio应用程序的创建经验
Fernanda Adães Britto,Juliana Paranhos Moreno Batista,Fabiana Lustosa Gaspar et al.
Fernanda Adães Britto et al.
This article describes the digital transformation trajectory of the Municipal Health Department of Rio de Janeiro (SMS-Rio), leading to the creation of minhasaude.rio application. The study was divided into two phases: document analysis and...
Telephysiotherapy in the Brazilian Unified Health System: an experience in the Central-West region [0.03%]
巴西统一卫生系统远程物理治疗：中西部地区的经验
Núria Ananda Parron Giacomelli Pereira,Datiene Aparecida Diniz Rodrigues Bernal,Bruno Cardoso Dantas et al.
Núria Ananda Parron Giacomelli Pereira et al.
This study describes the implementation of telerehabilitation in the Brazilian Unified Health System (SUS) in a Midwestern municipality, characterizing the profile of users referred by Primary Health Care, musculoskeletal demands, and clini...
Observational Study
Ciencia & saude coletiva. 2026 May;31(5):e00262026. DOI:10.1590/1413-81232026315.00262026 2026
Analysis of patterns of violence against women in Brazil: an unsupervised machine learning approach [0.03%]
巴西针对妇女暴力行为模式的分析：一种无监督机器学习方法
Andre Massahiro Shimaoka,Antonio Carlos da Silva Junior,José Marcio Duarte et al.
Andre Massahiro Shimaoka et al.
Analyze patterns of association between diagnoses related to domestic violence in hospital admissions and identify clinical-demographic profiles using unsupervised machine learning. Data from the SUS Hospital Information System between 2008...