Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Jacob Rivera"'
Autor:
Sena Veazey, Nicole Caldwell, David Luellen, Angela Samosorn, Allison McGlasson, Patricia Colston, Craig Fenrich, Jose Salinas, Jared Mike, Jacob Rivera, Maria Serio-Melvin
Publikováno v:
BioMedInformatics, Vol 4, Iss 1, Pp 709-720 (2024)
Critical care injuries, such as burn trauma, require specialized skillsets and knowledge. A clinical decision support system to aid clinicians in providing burn patient management can increase proficiency and provide knowledge content for specific in
Externí odkaz:
https://doaj.org/article/3b9328aa72d1417280ede7f79fe4d9e8
Publikováno v:
Summa, Vol 2, Iss Especial (2020)
El estudio consistió en desarrollar un modelo didáctico, innovador e inclusivo para el desarrollo de la educación en tecnología mediante la construcción de objetos tecnológicos en educación media, para responder a la pandemia de COVID 19. Teó
Externí odkaz:
https://doaj.org/article/222cad6f14e14ea0b62edfffb394c19c
Publikováno v:
Hexágono Pedagógico, Vol 9, Iss 1 (2018)
Las universidades han sido consideradas como instituciones generadoras y difusoras de nuevos conocimientos científicos y tecnológicos, siendo la investigación la fuente principal de estos conocimientos, los cuales deben ser gestionados para su cre
Externí odkaz:
https://doaj.org/article/f3f2af053cd7491da471762b8482f62a
Publikováno v:
Applied Sciences, Vol 11, Iss 8, p 3509 (2021)
Comparing data objects is at the heart of machine learning. For continuous data, object dissimilarity is usually taken to be object distance; however, for categorical data, there is no universal agreement, for categories can be ordered in several dif
Externí odkaz:
https://doaj.org/article/403359bbf997416aaf43a79a0c76eda3
Publikováno v:
Proceedings of the 16th ACM International Conference on Distributed and Event-Based Systems.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f19a520af4ca00302bcda9ac85b1ca57
https://doi.org/10.1145/3524860.3539651
https://doi.org/10.1145/3524860.3539651
Publikováno v:
Applied Sciences
Volume 11
Issue 8
Applied Sciences, Vol 11, Iss 3509, p 3509 (2021)
Volume 11
Issue 8
Applied Sciences, Vol 11, Iss 3509, p 3509 (2021)
Comparing data objects is at the heart of machine learning. For continuous data, object dissimilarity is usually taken to be object distance
however, for categorical data, there is no universal agreement, for categories can be ordered in several
however, for categorical data, there is no universal agreement, for categories can be ordered in several
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e249e049ff4928c3d0ccbff00991d641