Classification of gastric emptying and orocaecal transit through artificial neural networks

Classification of gastric emptying and orocaecal transit through artificial neural networks

Classical quantification of gastric emptying (GE) and orocaecal transit (OCT) based on half-life time T50, mean gastric emptying time (MGET), orocaecal transit time (OCTT) or mean caecum arrival time (MCAT) can lead to misconceptions when analyzing irregularly or noisy data. We show that this is the...

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Detalles Bibliográficos
Autores principales: Anibal Thiago Bezerra, Leonardo Antonio Pinto, Diego Samuel Rodrigues, Gabriela Nogueira Bittencourt, Paulo Fernando de Arruda Mancera, José Ricardo de Arruda Miranda
Formato: article
Lenguaje:EN
Publicado: AIMS Press 2021
Materias:
gastric emptying
experimental diabetes mellitus
orocaecal transit
deep learning
artificial intelligence
Biotechnology
TP248.13-248.65
Mathematics
QA1-939
Acceso en línea:https://doaj.org/article/9d6b1d25281b4d0c9564aee302b36694
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https://doaj.org/article/9d6b1d25281b4d0c9564aee302b36694

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