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...

Full description

Saved in:
Bibliographic Details
Main Authors: Anibal Thiago Bezerra, Leonardo Antonio Pinto, Diego Samuel Rodrigues, Gabriela Nogueira Bittencourt, Paulo Fernando de Arruda Mancera, José Ricardo de Arruda Miranda
Format: article
Language:EN
Published: AIMS Press 2021
Subjects:
gastric emptying
experimental diabetes mellitus
orocaecal transit
deep learning
artificial intelligence
Biotechnology
TP248.13-248.65
Mathematics
QA1-939
Online Access:https://doaj.org/article/9d6b1d25281b4d0c9564aee302b36694
Tags: Add Tag
No Tags, Be the first to tag this record!
Be the first to leave a comment!
You must be logged in first

Similar Items