AIMC Topic: Brazil
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Natural language processing in at-risk mental states: enhancing the assessment of thought disorders and psychotic traits with semantic dynamics and graph theory.
Revista brasileira de psiquiatria (Sao Paulo, Brazil : 1999)
Jul 29, 2024
OBJECTIVE: Verbal communication contains key information for mental health assessment. Researchers have linked psychopathology phenomena to certain counterparts in natural language processing. We characterized subtle impairments in the early stages o...
Comparative Analysis of Milking and Behavior Characteristics of Multiparous and Primiparous Cows in Robotic Systems.
Anais da Academia Brasileira de Ciencias
Jul 19, 2024
Robotic milking systems are successful innovations in the development of dairy cattle. The objective of this study was to analyse the milking characteristics and behavior of dairy cows of different calving orders in "milk first" robotic milking syste...
Innovative infrastructure to access Brazilian fungal diversity using deep learning.
PeerJ
Jul 9, 2024
In the present investigation, we employ a novel and meticulously structured database assembled by experts, encompassing macrofungi field-collected in Brazil, featuring upwards of 13,894 photographs representing 505 distinct species. The purpose of ut...
Recognition of Patient Gender: A Machine Learning Preliminary Analysis Using Heart Sounds from Children and Adolescents.
Pediatric cardiology
Jun 27, 2024
Research has shown that X-rays and fundus images can classify gender, age group, and race, raising concerns about bias and fairness in medical AI applications. However, the potential for physiological sounds to classify sociodemographic traits has no...
Determination of prognostic markers for COVID-19 disease severity using routine blood tests and machine learning.
Anais da Academia Brasileira de Ciencias
Jun 24, 2024
The need for the identification of risk factors associated to COVID-19 disease severity remains urgent. Patients' care and resource allocation can be potentially different and are defined based on the current classification of disease severity. This ...
Study of machine learning techniques for outcome assessment of leptospirosis patients.
Scientific reports
Jun 17, 2024
Leptospirosis is a global disease that impacts people worldwide, particularly in humid and tropical regions, and is associated with significant socio-economic deficiencies. Its symptoms are often confused with other syndromes, which can compromise cl...
Artificial intelligence enables unified analysis of historical and landscape influences on genetic diversity.
Molecular phylogenetics and evolution
Jun 12, 2024
While genetic variation in any species is potentially shaped by a range of processes, phylogeography and landscape genetics are largely concerned with inferring how environmental conditions and landscape features impact neutral intraspecific diversit...
Use of machine learning to identify protective factors for death from COVID-19 in the ICU: a retrospective study.
PeerJ
Jun 12, 2024
BACKGROUND: Patients in serious condition due to COVID-19 often require special care in intensive care units (ICUs). This disease has affected over 758 million people and resulted in 6.8 million deaths worldwide. Additionally, the progression of the ...
Utilization of machine learning for dengue case screening.
BMC public health
Jun 11, 2024
Dengue causes approximately 10.000 deaths and 100 million symptomatic infections annually worldwide, making it a significant public health concern. To address this, artificial intelligence tools like machine learning can play a crucial role in develo...
Predicting the pulse of the Amazon: Machine learning insights into deforestation dynamics.
Journal of environmental management
Jun 4, 2024
This study aims to analyze deforestation in the Brazilian Amazon from 1999 to 2020 using machine learning techniques to assess 16 critical factors. Our approach leverages the capabilities of machine learning, particularly Random Forest, which proved ...
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