Objectives: Nowadays breath test, using the Ghoss method for the calculation of gastric emptying of solids, is characterized by a very high number of expirations in a very long time (about 4 hours). In this work, a simplified model aiming to the reduction of the number of expirations during this time was designed, preserving high levels of accuracy, sensitivity and specificity in the classification between 'normal' or 'delayed' gastric emptying. Materials and Methods: Materials consist of 238 breath test exams from 66 different patients; for each exam, the relevance of each expiration was evaluated. Several models were designed and tested comparing their performance with a full model which took into account 17 expirations; among them, the model with the highest accuracy was selected: it consists of 7 expirations (baseline, 75, 135, 195, 210, 225 and 240 min). Results: Considering the previous model, the number of expirations was reduced by 62.5 %, still reaching high levels of accuracy, sensitivity and specificity (about 90 %) comparable with the full model which showed an accuracy of 98 %. Conclusion: The adoption of the proposed model led to a considerable reduction of required expirations, still having good performance in classifying 'normal' and 'delayed' gastric emptying. At the same time, since it requires fewer breaths, test was also simplified, allowing patients to do this exam at home. Furthermore, the reduction of breaths led to a considerable cost reduction of the entire examination.
|Titolo:||Analysis and optimization of the 13C octanoic acid breath test|
|Data di pubblicazione:||2017|
|Nome del convegno:||International Joint Conference on Neural Networks, IJCNN 2017|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1109/IJCNN.2017.7966430|
|Appare nelle tipologie:||4.1 Contributo in Atti di convegno|