AIMC Topic: Brazil
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Indices of dietary fat quality during midpregnancy is associated with gestational diabetes.
Nutrition (Burbank, Los Angeles County, Calif.)
Dec 18, 2015
OBJECTIVE: To investigate the relationship between gestational diabetes mellitus (GDM) and the usual intake of fatty acids and indices of dietary fat quality [the atherogenicity (AI) and thrombogenicity indices (TI), and the ratios of hypo-and hyperc...
Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data.
Journal of integrative bioinformatics
Oct 21, 2015
Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plant's resin, but a big...
Predictive modeling based on machine learning for mapping risk areas of human sporotrichosis in southeastern Brazil.
Research in veterinary science
Jul 1, 2025
Sporotrichosis, a zoonotic mycosis with a growing public health impact, requires innovative methods to map risk areas. This study applied machine learning techniques, Artificial Neural Networks (ANN), and Decision Trees (DT) to integrate sociodemogra...
Improving the mapping of leisure-time physical activity inequities: the use of artificial intelligence to advance estimates of small-areas in Brazil.
Public health
Jun 1, 2025
OBJECTIVE: We estimated the prevalence of leisure-time physical activity (LTPA) in small areas of the city of Belo Horizonte and analyzed inequities across areas and between two time periods, 2009-2013 and 2014-2018.
Amazon's climate crossroads: analyzing air pollution and health impacts under machine learning-based temperature increase scenarios in Northern Mato Grosso, Brazil.
Environmental geochemistry and health
May 14, 2025
Air pollution has long been a public health concern in South America, now increasingly linked to climate change. In Brazil, this issue is particularly acute in smaller cities with limited monitoring infrastructure. Sinop, located in the Amazon biome ...
Predicting health literacy in Brazil: a machine learning approach.
Health promotion international
May 13, 2025
Health literacy is essential for promoting well-being and the ability to make informed decisions. We investigated the level of health literacy in Brazil and identified the predictive factors that influence it. Our data contribute to the international...
Heart failure risk stratification using artificial intelligence applied to electrocardiogram images: a multinational study.
European heart journal
Mar 13, 2025
BACKGROUND AND AIMS: Current heart failure (HF) risk stratification strategies require comprehensive clinical evaluation. In this study, artificial intelligence (AI) applied to electrocardiogram (ECG) images was examined as a strategy to predict HF r...
Machine learning algorithm approach to complete blood count can be used as early predictor of COVID-19 outcome.
Journal of leukocyte biology
Feb 13, 2025
Although the SARS-CoV-2 infection has established risk groups, identifying biomarkers for disease outcomes is still crucial to stratify patient risk and enhance clinical management. Optimal efficacy of COVID-19 antiviral medications relies on early a...
An exploration of current and future vector-borne disease threats and opportunities for change.
Frontiers in public health
Jan 1, 2025
Vector-borne diseases, including dengue, threaten the health and livelihoods of over 80% of the world's population, particularly in tropical and subtropical regions. Environmental, ecological, climatic, and socio-economic factors are expected to driv...
Artificial intelligence-enabled electrocardiogram for mortality and cardiovascular risk estimation: a model development and validation study.
The Lancet. Digital health
Nov 1, 2024
BACKGROUND: Artificial intelligence (AI)-enabled electrocardiography (ECG) can be used to predict risk of future disease and mortality but has not yet been adopted into clinical practice. Existing model predictions do not have actionability at an ind...
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