Machine Learning Model Based on Lipidomic Profile Information to Predict Sudden Infant Death Syndrome by Karen E. Villagrana-Bañuelos, Carlos E. Galván-Tejada, Jorge I. Galván-Tejada, Hamurabi Gamboa-Rosales, José M. Celaya-Padilla, Manuel A. Soto-Murillo, Roberto Solís-Robles

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Univariate Analysis of Short-Chain Fatty Acids Related to Sudden Infant Death Syndrome by Carlos E. Galván-Tejada, Karen E. Villagrana-Bañuelos, Laura A. Zanella-Calzada, Arturo Moreno-Báez, Huizilopoztli Luna-García, Jose M. Celaya-Padilla, Jorge I. Galván-Tejada, Hamurabi Gamboa-Rosales

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Kynurenine and Hemoglobin as Sex-Specific Variables in COVID-19 Patients: A Machine Learning and Genetic Algorithms Approach by Jose M. Celaya-Padilla, Karen E. Villagrana-Bañuelos, Juan José Oropeza-Valdez, Joel Monárrez-Espino, Julio E. Castañeda-Delgado, Ana Sofía Herrera-Van Oostdam, Julio César Fernández-Ruiz, Fátima Ochoa-González, Juan Carlos Borrego, Jose Antonio Enciso-Moreno, Jesús Adrián López, Yamilé López-Hernández, Carlos E. Galván-Tejada

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COVID-19 outcome prediction by integrating clinical and metabolic data using machine learning algorithms by Karen E. Villagrana-Bañuelos, Valeria Maeda-Gutiérrez, Vanessa Alcalá-Rmz, Juan J. Oropeza-Valdez, Ana S. Herrera-Van Oostdam, Julio E. Castañeda-Delgado, Jesús Adrián López, Juan C. Borrego Moreno, Carlos E. Galván-Tejada, Jorge I. Galván-Tejeda, Hamurabi Gamboa-Rosales, Huizilopoztli Luna-García, José M. Celaya-Padilla, Yamilé López-Hernández

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