AIMC Topic: Brazil

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MAIA platform for routine clinical testing: an artificial intelligence embryo selection tool developed to assist embryologists.

Scientific reports
The need to reduce the number of embryos transferred in assisted reproductive care to prevent multiple gestations has led to a stronger emphasis on selecting embryos with the highest morphological quality. Although this evaluation has traditionally b...

Unveiling the hidden burden of COVID-19 in Brazil's obstetric population with severe acute respiratory syndrome: A machine learning model.

PloS one
OBJECTIVE: To predict the actual number of COVID-19 cases in Brazilian pregnant and postpartum women diagnosed with Severe Acute Respiratory Syndrome using a predictive model created based on data from Brazilian database.

Bridging the predictive divide: A hybrid early warning system for scalable and real-time dengue surveillance in LMICs.

Acta tropica
The global resurgence of dengue presents an ongoing challenge for public health systems, particularly in low- and middle-income countries (LMICs) where conventional early warning systems (EWS) often suffer from reporting delays and under-detection. W...

Machine learning-based prediction of nitrogen-fixing efficiency in Cowpea rhizobia from the Brazilian semiarid.

World journal of microbiology & biotechnology
This study explores the potential of machine learning to predict nitrogen fixation efficiency in rhizobia strains associated with cowpea (Vigna unguiculata), aiming to optimize bioinoculant selection for sustainable agriculture. Eight native strains ...

Oropouche fever outbreak in Brazil: Key factors behind the largest epidemic in history.

PloS one
Oropouche virus (OROV) is an arthropod-borne virus responsible for outbreaks of Oropouche fever (ORO) in Central and South America since the 1950s. Herein, we investigated the climatic and socioenvironmental factors contributing to the reemergence of...

Artificial intelligence platform to predict children's hospital care for respiratory disease using clinical, pollution, and climatic factors.

Journal of global health
BACKGROUND: Hospitals and health care systems may benefit from artificial intelligence (AI) and big data to analyse clinical information combined with external sources. Machine learning, a subset of AI, uses algorithms trained on data to generate pre...

Developing the CAM-BERT: Enhancing delirium screening in hospitalized older adults using natural language processing.

Computers in biology and medicine
BACKGROUND: Delirium is a common condition affecting hospitalized older adults, often leading to adverse outcomes. Nevertheless, delirium frequently goes unrecognized due to various clinical and systemic challenges. We aimed to develop and evaluate a...

Predictive modelling of land use land cover dynamics for a coastal urban city in Brazil.

Journal of environmental management
Better urban planning depends on assessing how land use and land cover (LULC) have evolved in recent decades and what the prospects are for change in the future. Cities are the result of various factors interacting, and land configuration directly in...

Predictive estimations of health systems resilience using machine learning.

BMC medical informatics and decision making
Operationalizing resilience in public health systems is critical for enhancing adaptive capacity during crises. This study presents a Machine Learning (ML) -based approach to assess resilience of the health system. Using historical data from Brazilia...