Appetite ratings of foods are predictable with an in vitro advanced gastrointestinal model in combination with an in silico artificial neural network-Reference-Cited by-同舟云学术

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Appetite ratings of foods are predictable with an in vitro advanced gastrointestinal model in combination with an in silico artificial neural network

Published:2019-08 Issue: Volume:122 Page:77-86
ISSN:0963-9969
Container-title:Food Research International
language:en
Short-container-title:Food Research International

Author:

Bellmann Susann,Krishnan Shaji,de Graaf Albert,de Ligt Rianne A.,Pasman Wilrike J.,Minekus Mans,Havenaar Robert

Funder

Dutch Ministry of Economic Affairs, Agriculture and Innovation

Netherlands Bakery Center

Quaker Oats Center of Excellence

PepsiCo R&D Nutrition Sciences

TNO

Triskelion in a Public Private Partnership

Publisher

Elsevier BV

Subject

Food Science

Reference43 articles.

1. In vitro measurements of luminal viscosity and glucose/maltose bioaccessibility for oat bran, instant oats, and steel cut oats;AlHasawi;Food Hydrocoloids,2017

2. Application and validation of an advanced gastrointestinal in vitro model for the evaluation of drug product performance in pharmaceutical development;Barker;Journal of Pharmaceutical Sciences,2014

3. Application of artificial neuronal networks to clinical medicine;Baxt;Lancet,1995

4. Development of an advanced in vitro model of the stomach and its evaluation versus human gastric physiology;Bellmann;Food Research International,2016

5. Human glycemic response curves after intake of carbohydrate foods are accurately predicted by combining in vitro gastrointestinal digestion with in silico kinetic modeling;Bellmann;Clinical Nutrition Experimental,2018

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