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Using machine learning to estimate health spillover effects.

The European journal of health economics : HEPAC : health economics in prevention and care
We develop a nonparametric model to study health spillover effects of policy interventions. We use double/debiased machine learning to estimate the model using data from 74 hospitals in Rio de Janeiro, Brazil, and examine cross-patient spillover effe...

Environmental vulnerability evolution in the Brazilian Amazon.

Anais da Academia Brasileira de Ciencias
Decision making and environmental policies are mainly based on propensity level to impact in the area. The propensity level can be determined through artificial intelligence techniques included in geotechnological universe. Thus, this study aimed to ...

Traffic Sign Recognition with Deep Learning: Vegetation Occlusion Detection in Brazilian Environments.

Sensors (Basel, Switzerland)
Traffic Sign Recognition (TSR) is one of the many utilities made possible by embedded systems with internet connections. Through the usage of vehicular cameras, it's possible to capture and classify traffic signs in real time with Artificial Intellig...

Predicting congenital syphilis cases: A performance evaluation of different machine learning models.

PloS one
BACKGROUND: Communicable diseases represent a huge economic burden for healthcare systems and for society. Sexually transmitted infections (STIs) are a concerning issue, especially in developing and underdeveloped countries, in which environmental fa...

Machine learning for predicting survival of colorectal cancer patients.

Scientific reports
Colorectal cancer is one of the most incident types of cancer in the world, with almost 2 million new cases annually. In Brazil, the scenery is the same, around 41 thousand new cases were estimated in the last 3 years. This increase in cases further ...

Use of machine learning as a tool for determining fire management units in the brazilian atlantic forest.

Anais da Academia Brasileira de Ciencias
Geoprocessing techniques are generally applied in natural disaster risk management due to their ability to integrate and visualize different sets of geographic data. The objective of this study was to evaluate the capacity of classification and regre...

Impact on the ability of healthcare professionals to correctly identify patient-ventilator asynchronies of the simultaneous visualization of estimated muscle pressure curves on the ventilator display: a randomized study (P study).

Critical care (London, England)
BACKGROUND: Patient-ventilator asynchronies are usually detected by visual inspection of ventilator waveforms but with low sensitivity, even when performed by experts in the field. Recently, estimation of the inspiratory muscle pressure (P) waveforms...

Authentication of beef cuts by multielement and machine learning approaches.

Journal of trace elements in medicine and biology : organ of the Society for Minerals and Trace Elements (GMS)
BACKGROUND: Brazil has consolidated a relevant position in the world market, being the largest exporter and second producer of beef. Genetics, feeding system, geographic origin and climate influence the multielement profile of beef. The feasibility o...

Emergency department use and Artificial Intelligence in Pelotas: design and baseline results.

Revista brasileira de epidemiologia = Brazilian journal of epidemiology
OBJETIVO: To describe the initial baseline results of a population-based study, as well as a protocol in order to evaluate the performance of different machine learning algorithms with the objective of predicting the demand for urgent and emergency s...

Active Actions in the Extraction of Urban Objects for Information Quality and Knowledge Recommendation with Machine Learning.

Sensors (Basel, Switzerland)
Due to the increasing urban development, it has become important for municipalities to permanently understand land use and ecological processes, and make cities smart and sustainable by implementing technological tools for land monitoring. An importa...