AIMC Topic: Brazil

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Explainable few-shot learning workflow for detecting invasive and exotic tree species.

Scientific reports
Deep Learning methods are notorious for relying on extensive labeled datasets to train and assess their performance. This can cause difficulties in practical situations where models should be trained for new applications for which very little data is...

Quality assessment of large language models' output in maternal health.

Scientific reports
Optimising healthcare is linked to broadening access to health literacy in Low- and Middle-Income Countries. The safe and responsible deployment of Large Language Models (LLMs) may provide accurate, reliable, and culturally relevant healthcare inform...

Mitochondrial haplogroup A2 is associated with increased COVID-19 mortality in an admixed Brazilian population.

Scientific reports
Mitochondria play a crucial role in cellular respiration and immune responses. Mitochondrial DNA (mtDNA) haplogroups and variants have been associated with various diseases, including COVID-19. This study analyzed complete mtDNA sequences from 467 Br...

Accuracy of Artificial Intelligence for Gatekeeping in Referrals to Specialized Care.

JAMA network open
IMPORTANCE: Integrating artificial intelligence (AI) technologies into gatekeeping holds significant potential, as it efficiently handles repetitive tasks and can process large amounts of information quickly.

[Cluster predictors of trajectories of leisure-time physical activity intensity in men and women from ELSA-Brasil].

Cadernos de saude publica
The maintenance of physical activity over time is a challenge for public health. Predictors of different physical activity intensities have not been sufficiently analyzed. This study aimed to identify clusters of trajectories of physical activity int...

An investigation into the impact of temporality on COVID-19 infection and mortality predictions: new perspective based on Shapley Values.

BMC medical research methodology
INTRODUCTION: Machine learning models have been employed to predict COVID-19 infections and mortality, but many models were built on training and testing sets from different periods. The purpose of this study is to investigate the impact of temporali...

Combining machine learning and dynamic system techniques to early detection of respiratory outbreaks in routinely collected primary healthcare records.

BMC medical research methodology
BACKGROUND: Methods that enable early outbreak detection represent powerful tools in epidemiological surveillance, allowing adequate planning and timely response to disease surges. Syndromic surveillance data collected from primary healthcare encount...

Analysing similarities between legal court documents using natural language processing approaches based on transformers.

PloS one
Recent advancements in Artificial Intelligence have yielded promising results in addressing complex challenges within Natural Language Processing (NLP), serving as a vital tool for expediting judicial proceedings in the legal domain. This study focus...

AI models uncover factors influencing scorpionism in Northern Brazil.

Toxicon : official journal of the International Society on Toxinology
Envenomation by scorpion stings is a serious public health problem in tropical regions of the world. In Brazil's Northern region, there has been a significant increase in cases over the last decade, accompanied by a rise in the fatality rate. Climate...