Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Ramon E. Diaz-Ramos"'
Autor:
Daniela A. Gomez-Cravioto, Ramon E. Diaz-Ramos, Neil Hernandez-Gress, Jose Luis Preciado, Hector G. Ceballos
Publikováno v:
Journal of Big Data, Vol 9, Iss 1, Pp 1-31 (2022)
Abstract Background This paper explores machine learning algorithms and approaches for predicting alum income to obtain insights on the strongest predictors and a ‘high’ earners’ class. Methods It examines the alum sample data obtained from a s
Externí odkaz:
https://doaj.org/article/784c155b613f470299e4a8bff1db4f4f
Autor:
Ramon E. Diaz-Ramos, Daniela A. Gomez-Cravioto, Luis A. Trejo, Carlos Figueroa López, Miguel Angel Medina-Pérez
Publikováno v:
Sensors, Vol 21, Iss 24, p 8293 (2021)
This study proposes a new index to measure the resilience of an individual to stress, based on the changes of specific physiological variables. These variables include electromyography, which is the muscle response, blood volume pulse, breathing rate
Externí odkaz:
https://doaj.org/article/ca178fda1ccc488c964022e9731cab03
Publikováno v:
JMIR Research Protocols, Vol 12, p e48210 (2023)
BackgroundEarly identification of mental disorder symptoms is crucial for timely treatment and reduction of recurring symptoms and disabilities. A tool to help individuals recognize warning signs is important. We posit that such a tool would have to
Externí odkaz:
https://doaj.org/article/8198dcbed7784c7ca8e4e73714698124
BACKGROUND Early detection of mental disorders symptoms can lead to prompt and correct diagnosis and reduce the recurrence of these symptoms and associated disabilities. Creating a tool to detect early symptoms is crucial for taking the necessary mea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d0bd6c2691bf62bf9cfe97d17980ca90
https://doi.org/10.2196/preprints.48210
https://doi.org/10.2196/preprints.48210
Autor:
Neil Hernandez Gress, Hector G. Ceballos, Daniela A. Gomez-Cravioto, Ramon E. Diaz-Ramos, Jose Luis Preciado
Publikováno v:
Journal of Big Data, Vol 9, Iss 1, Pp 1-31 (2022)
Background: This paper explores different machine learning algorithms and approaches for predicting alum income to obtain insights on the strongest predictors for income and a ‘high’ earners’ class. Methods: The study examines the alum sample d
Publikováno v:
Cognitive Computation
To understand and approach the spread of the SARS-CoV-2 epidemic, machine learning offers fundamental tools. This study presents the use of machine learning techniques for projecting COVID-19 infections and deaths in Mexico. The research has three ma
Background: To understand and approach the COVID-19 spread, Machine Learning offers fundamental tools. This study presents the use of machine learning techniques for the projection of COVID-19 infections and deaths in Mexico. The research has three m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ddb516b86118af77e826b14c535f9606
https://doi.org/10.21203/rs.3.rs-62035/v1
https://doi.org/10.21203/rs.3.rs-62035/v1