A. Zifan, Junyue Lin, Zihan Peng, Yiqing Bo, R. Mittal
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引用次数: 0
Abstract
(1) Background: Dysphagia affects around 16% of the US population. Diagnostic tests like X-ray barium swallow and endoscopy are used initially to diagnose the cause of dysphagia, followed by high-resolution esophageal manometry (HRM). If the above tests are normal, the patient is classified as functional dysphagia (FD), suggesting esophageal sensory dysfunction. HRM records only the contraction phase of peristalsis, not the distension phase. We investigated the utilization of esophageal distension–contraction patterns for the automatic classification of FD, using artificial intelligent shallow learners. (2) Methods: Studies were performed in 30 healthy subjects and 30 patients with FD. Custom-built software (Dplots 1.0) was used to extract relevant esophageal distension–contraction features. Next, we used multiple shallow learners, namely support vector machines, random forest, K-nearest neighbors, and logistic regression, to determine which had the best performance in terms of accuracy, precision, and recall. (3) Results: In the proximal segment, LR produced the best results, with accuracy of 91.7% and precision of 92.86%, using only distension features. In the distal segment, random forest produced accuracy of 90.5% and precision of 91.1% using both pressure and distension features. (4) Conclusions: Findings emphasize the crucial role of abnormality in the distension phase of peristalsis in FD patients.
期刊介绍:
Applied Sciences (ISSN 2076-3417) provides an advanced forum on all aspects of applied natural sciences. It publishes reviews, research papers and communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. Electronic files and software regarding the full details of the calculation or experimental procedure, if unable to be published in a normal way, can be deposited as supplementary electronic material.