Natalia da Silva

Student performance and LMS activity in primary schools: a Bayesian additive regression trees approach with random effects

Natalia da Silva, Bruno Tancredi, Ignacio Alvarez-Castro

uy (code pays fourni par la source)

Registros sociales y aprendizaje estadístico: respuestas oportunas para gestantes y niñez temprana en Uruguay

Elina Gómez Bonaglia, Gustavo Méndez Barbato, P Rimbaud, Natalia da Silva

Este artículo analiza el potencial de la integración de registros sociales y la capacidad predictiva de los modelos basados en aprendizaje estadístico para mejorar la oportunidad y efectividad de las políticas sociales dirigidas a gestantes y niñez temprana en Uruguay. Ante la …

uy (code pays fourni par la source)

PERFIL EPIDEMIOLÓGICO DE CANDIDATOS A TRANSPLANTE DE CÉLULAS-TRONCO HEMATOPOÉTICAS (TCTH) NA REGIÃO NORTE DO BRASIL (2022-2025)

Rui Oliveira, Natalia da Silva, E. Ramos, Patrícia Jeanne de Souza Mendonça Mattos

O TCTH constitui modalidade terapêutica curativa para diversas neoplasias hematológicas, imunodeficiências primárias e hemoglobinopatias.[1] No Brasil, a região Norte apresenta particularidades epidemiológicas únicas, incluindo alta miscigenação étnica e prevalência elevada de hemoglobinopatias, fatores que influenciam diretamente a compatibilidade HLA.[2] A análise do …

Large scale study of primary school student performance relative to their LMS activity and socioeconomic demographics using a Bayesian Additive Regression Trees containing random effects

Natalia da Silva, Bruno Tancredi, Ignacio Alvarez-Castro

Using data collected on almost every 9-12 years old student in Uruguay, we show how to apply Bayesian Additive Regression Trees (BART) with random effects to study performance association with Learning Managment System (LMS) activity and socioeconomic status. Performance data is joined …

SpICE: an interpretable method for spatial data

Natalia da Silva, Ignacio Alvarez-Castro, Leonardo Moreno, Andrés Sosa

uy (code pays fourni par la source)

Partnering With Authors to Enhance Reproducibility at JASA

Julia Wrobel, Emily C. Hector, Lorin Crawford, Lucy D’Agostino McGowan et autres

1 IntroductionIn 2016, JASA Applications and Case Studies (ACS) introduced a reproducibility initiative to address the lack of standardized practices for reproducibility in scientific research. Thi...

us, gb, uy, br, th (code pays fourni par la source)

SpICE: An interpretable method for spatial data

Natalia da Silva, Ignacio Alvarez-Castro, Leonardo Moreno, Andrés Sosa

Statistical learning methods are widely utilized in tackling complex problems due to their flexibility, good predictive performance and its ability to capture complex relationships among variables. Additionally, recently developed automatic workflows have provided a standardized approach to implementing statistical learning methods across …

Programa stewardship de antimicrobianos de uso restrito em idosos: estudo de coorte em um hospital quaternário do Brasil

Natalia da Silva, Angélica Caroline Ferreira, Thauane Pereira Nunes, Maria Eduarda MORET et autres

Objetivo: A estratégia denominada stewardship refere-se a um conjunto de intervenções coerentes direcionadas a promover o uso responsável de antimicrobianos. A otimização do uso de antibióticos é fundamental para tratar de forma correta as infecções, mitigar efeitos adversos aos pacientes e combater …

br (code pays fourni par la source)

Interactive graphics for visually diagnosing forest classifiers in R

Natalia da Silva, Dianne Cook, Eun‐Kyung Lee

uy, au, kr (code pays fourni par la source)

p63 Controls Metabolic Activation of Hepatic Stellate Cells and Fibrosis via ACC1

Marcos F. Fondevila, Eva Nóvoa, María J. Gonzalez-Rellan, Uxia Fernandez et autres

es, fr, de, us, cz, hr (code pays fourni par la source)

Aprendizaje estadístico interpretable: una aplicación al precio de inmuebles en Montevideo, Uruguay (interpretable statistical learning: an application to property prices in Montevideo, Uruguay)

Ignacio Alvarez-Castro, Natalia da Silva, Leonardo Moreno, Andrés Sosa

Supervised statistical learning techniques have been developed over the time in very diverse lines of research and in a great variety of problems applied. These methods are mainly used in order to predict its response. to new data in complex problems due …

uy, cl (code pays fourni par la source)

Intersection between environmental data science and the R community in Latin America

Natalia da Silva

Abstract Environmental data science is used to solve environmental problems, and to help answer complex questions about biodiversity loss, climate change, and water scarcity, among others thereby allowing sustainable decision‐making using data‐driven approaches. In this opinion piece, I describe some recent Latin …

uy (code pays fourni par la source)