Zobrazeno 1 - 4 of 4 pro vyhledávání: '"Luisa Fernanda Jimenez-Alvarez"'
1
Multinational Prospective Cohort Study of Mortality Risk Factors in 198 ICUs of 12 Latin American Countries over 24 Years: The Effects of Healthcare-Associated Infections
Autor: Victor Daniel Rosenthal, Ruijie Yin, Sandra Liliana Valderrama-Beltran, Sandra Milena Gualtero, Claudia Yaneth Linares, Guadalupe Aguirre-Avalos, Julio Cesar Mijangos-Méndez, Miguel Ángel Ibarra-Estrada, Luisa Fernanda Jimenez-Alvarez, Lidia Patricia Reyes, Carlos Arturo Alvarez-Moreno, Maria Adelia Zuniga-Chavarria, Ana Marcela Quesada-Mora, Katherine Gomez, Johana Alarcon, Jose Millan Oñate, Daisy Aguilar-De-Moros, Elizabeth Castaño-Guerra, Judith Córdoba, Alejandro Sassoe-Gonzalez, Claudia Marisol Millán-Castillo, Lissette Leyva Xotlanihua, Lina Alejandra Aguilar-Moreno, Juan Sebastian Bravo Ojeda, Ivan Felipe Gutierrez Tobar, Mary Cruz Aleman-Bocanegra, Clara Veronica Echazarreta-Martínez, Belinda Mireya Flores-Sánchez, Yuliana Andrea Cano-Medina, Edwin Giovannny Chapeta-Parada, Rafael Antonio Gonzalez-Niño, Maria Isabel Villegas-Mota, Mildred Montoya-Malváez, Miguel Ángel Cortés-Vázquez, Eduardo Alexandrino Medeiros, Dayana Fram, Daniela Vieira-Escudero, Zhilin Jin
Publikováno v: Journal of Epidemiology and Global Health. 12:504-515
Background The International Nosocomial Infection Control Consortium (INICC) has found a high ICU mortality rate in Latin America. Methods A prospective cohort study in 198 ICUs of 96 hospitals in 46 cities in 12 Latin American countries to identify
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4d8ffd410ef609ed5528e9a8a355ab95
https://doi.org/10.1007/s44197-022-00069-x
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3
Renewable Energy Prediction through Machine Learning Algorithms
Autor: Luisa Fernanda Jimenez Alvarez, Antonio Delgado Lopez, Diego Alonso Hernandez Delgado, Sebastian Gutierrez, Sebastian Ramos Gonzalez, Ricardo Espinosa
Publikováno v: 2020 IEEE ANDESCON.
This paper aims to implement an efficient renewable energy selection (either solar or wind) based on the chosen geographic location of Aguascalientes, Mexico through a Machine Learning (ML) method. Likewise, the information listed below will provide
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2ab174344e075d24b5da43f180c4f0a3
https://doi.org/10.1109/andescon50619.2020.9272029
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Plný text Recenzováno Digitální knihovna AV ČR
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