COVID-19 outcome prediction by integrating clinical and metabolic data using machine learning algorithms

Autor: 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

Publikováno v: Revista de Investigación Clínica, Vol 74, Iss 6 (2022)

Background: The coronavirus disease (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus and is responsible for nearly 6 million deaths worldwide in the past 2 years. Machine learning (ML) models could help physicians in identifying hig

Externí odkaz: https://doaj.org/article/fb4644d06cea44b891e0dbdbdb0bdc37

Towards Esophagitis and Barret’s Esophagus Endoscopic Images Classification: An Approach with Deep Learning Techniques

Autor: Karen E. Villagrana-Bañuelos, Vanessa Alcalá-Rmz, José M. Celaya-Padilla, Jorge I. Galván-Tejada, Hamurabi Gamboa-Rosales, Carlos E. Galván-Tejada

Publikováno v: Proceedings of the International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2022) ISBN: 9783031213328

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::afb012d1f604246c25ea7e4c166f2b18
https://doi.org/10.1007/978-3-031-21333-5_17

Identification of People with Diabetes Treatment through Lipids Profile Using Machine Learning Algorithms

Autor: Miguel Cruz, José M. Celaya-Padilla, Carlos E. Galván-Tejada, Hamurabi Gamboa-Rosales, Jorge I. Galván-Tejada, Vanessa Alcalá-Rmz, Adan Valladares-Salgado, Alejandra García-Hernández, Huizilopoztli Luna-García

Publikováno v: Healthcare
Volume 9
Issue 4
Healthcare, Vol 9, Iss 422, p 422 (2021)

Diabetes incidence has been a problem, because according with the World Health Organization and the International Diabetes Federation, the number of people with this disease is increasing very fast all over the world. Diabetic treatment is important

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::37884efb65b007a3188e084513d9371e
http://europepmc.org/articles/PMC8067355

Identification of Diabetic Patients through Clinical and Para-Clinical Features in Mexico: An Approach Using Deep Neural Networks

Autor: Miguel Cruz, Vanessa Alcalá-Rmz, Hamurabi Gamboa-Rosales, Adan Valladares-Salgado, Laura A. Zanella-Calzada, Carlos E. Galván-Tejada, Alejandra García-Hernández, Jorge I. Galván-Tejada

Publikováno v: International Journal of Environmental Research and Public Health, Vol 16, Iss 3, p 381 (2019)
International Journal of Environmental Research and Public Health
Volume 16
Issue 3

Diabetes is a chronic and noncommunicable but preventable disease that is affecting the Mexican population at worrying levels, being the first place in prevalence worldwide. Early diabetes detection has become important to prevent other health condit

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0aefc99cbc007a6ed3f12a1523d630cc
https://www.mdpi.com/1660-4601/16/3/381