Iranian Journal of Biomedical Engineering (IJBME)
نشریه علمی مهندسی پزشکی زیستی

Distinguishing Multiple Concurrent Esophageal Motility Disorders using High-Resolution Manometry

Document Type : Full Research Paper

Authors

Safa Rafieivand 1
Mohammad Hassan Moradi 2
Zahra Momayez Sanat 3
Hosein Asl Soleimani 4

1 Ph.D. Student, Biomedical Engineering Department, Amirkabir University of Technology, Tehran, Iran

2 Professor, Biomedical Engineering Department, Amirkabir University of Technology, Tehran, Iran

3 Assistant Professor, Digestive Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran

4 Professor, Digestive Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran

https://doi.org/10.22041/ijbme.2023.2014226.1866
Abstract
Esophageal mobility disorders are a type of digestive system problem characterized by abnormal bolus movement in the esophagus. The standard diagnostic method for these kinds of disorders is High-Resolution Manometry (HRM). Despite the availability of guidelines like “Chicago” for the analysis of HRM results, diagnosis is still a challenging task that is relies on the physician's skills or requires additional assessment modalities. Additionally, it is typical for esophageal mobility disorders to co-occur in one person, leading to a more complex situation for problem identification. The current study focuses on cases who suffering from more than one disorder simultaneously. Then the problem of disorder identification can be interpreted as a multi-label classification problem. Consequently, the fuzzy classifier architecture that was previously introduced for automatic single-disorder diagnosis by the authors is modified. The presented classifier in this paper not only learns the input space from the samples but also utilizes the co-morbidity of disorders to enhance the prediction results. The outcomes show that adding this information to the learning procedure of the base classifier enhances its performance and generates a new fuzzy classifier that overcomes other multi-label classifiers. The presented method is able to differentiate esophageal mobility disorders with an average Hamming loss of 0.18±0.08 which is better than other competitor methods.

Keywords

Esophageal Manometry
Esophageal Mobility Disorders
Multi-Label Classification
Fuzzy Classification

Subjects

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Iranian Journal of Biomedical Engineering (IJBME)
Volume 17, Issue 2
Summer 2023
Pages 125-136

  • Receive Date 24 October 2023
  • Revise Date 20 November 2023
  • Accept Date 28 November 2023

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