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Deglutition

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Deep learning-based artificial intelligence model for identifying swallow types in esophageal high-resolution manometry.

Neurogastroenterology and motility
BACKGROUND: This study aimed to build and evaluate a deep learning, artificial intelligence (AI) model to automatically classify swallow types based on raw data from esophageal high-resolution manometry (HRM).

Prospectively-validated deep learning model for segmenting swallowing and chewing structures in CT.

Physics in medicine and biology
Delineating swallowing and chewing structures aids in radiotherapy (RT) treatment planning to limit dysphagia, trismus, and speech dysfunction. We aim to develop an accurate and efficient method to automate this process.CT scans of 242 head and neck ...

Deep Learning Analysis to Automatically Detect the Presence of Penetration or Aspiration in Videofluoroscopic Swallowing Study.

Journal of Korean medical science
BACKGROUND: Videofluoroscopic swallowing study (VFSS) is currently considered the gold standard to precisely diagnose and quantitatively investigate dysphagia. However, VFSS interpretation is complex and requires consideration of several factors. The...

Deep Learning for Automatic Hyoid Tracking in Videofluoroscopic Swallow Studies.

Dysphagia
The hyoid bone excursion is one of the most important gauges of larynx elevation in swallowing, contributing to airway protection and bolus passage into the esophagus. However, the implications of various parameters of hyoid bone excursion, such as t...

Development and validation of a chewing robot for mimicking human food oral processing and producing food bolus.

Journal of texture studies
More and more studies have being done on the deformation process of food and the formation of food bolus during chewing. However, it is hard to observe the food oral processing (FOP) of subjects and obtain related data directly. A bionic chewing robo...

A novel soft robotic pediatric in vitro swallowing device to gain insights into the swallowability of mini-tablets.

International journal of pharmaceutics
Soft robotics could help providing a better understanding of the mechanisms underpinning the swallowability of solid oral dosage forms (SODF), especially by vulnerable populations such as the elderly or children. In this study a novel soft robotic in...

A preliminary deep learning study on automatic segmentation of contrast-enhanced bolus in videofluorography of swallowing.

Scientific reports
Although videofluorography (VFG) is an effective tool for evaluating swallowing functions, its accurate evaluation requires considerable time and effort. This study aimed to create a deep learning model for automated bolus segmentation on VFG images ...

Detection of aspiration from images of a videofluoroscopic swallowing study adopting deep learning.

Oral radiology
OBJECTIVES: A videofluoroscopic swallowing study (VFSS) is conducted to detect aspiration. However, aspiration occurs within a short time and is difficult to detect. If deep learning can detect aspirations with high accuracy, clinicians can focus on ...

Autonomous Swallow Segment Extraction Using Deep Learning in Neck-Sensor Vibratory Signals From Patients With Dysphagia.

IEEE journal of biomedical and health informatics
Dysphagia occurs secondary to a variety of underlying etiologies and can contribute to increased risk of adverse events such as aspiration pneumonia and premature mortality. Dysphagia is primarily diagnosed and characterized by instrumental swallowin...

Application of deep learning technology for temporal analysis of videofluoroscopic swallowing studies.

Scientific reports
Temporal parameters during swallowing are analyzed for objective and quantitative evaluation of videofluoroscopic swallowing studies (VFSS). Manual analysis by clinicians is time-consuming, complicated and prone to human error during interpretation; ...