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A Machine Learning-Based Screening Test for Sarcopenic Dysphagia Using Image Recognition.

Kotomi Sakai1,2,3, Stuart Gilmour1, Eri Hoshino3

  • 1Graduate School of Public Health, St. Luke's International University, Tokyo 104-0044, Japan.

Nutrients
|November 27, 2021
PubMed
Summary
This summary is machine-generated.

A new image recognition screening test accurately identifies sarcopenic dysphagia, a swallowing disorder in older adults. This simple neck image analysis offers a low-risk method for early detection, potentially preventing malnutrition and pneumonia.

Keywords:
dysphagiaimage recognitionsarcopeniascreening

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Area of Science:

  • Gerontology
  • Medical Imaging
  • Swallowing Disorders

Background:

  • Sarcopenic dysphagia, a swallowing disorder linked to sarcopenia, affects many older adults.
  • It can lead to serious complications like malnutrition and aspiration pneumonia.
  • Current diagnostic methods may pose risks, such as droplet transmission.

Purpose of the Study:

  • To develop a simple, low-risk screening test for sarcopenic dysphagia.
  • To utilize image recognition of neck appearance for this screening.
  • To assess the prediction performance of the developed screening model.

Main Methods:

  • A cross-sectional study involving older patients in a post-acute care hospital.
  • Anterior neck photographs were taken to analyze image features (pixel values, feature points).
  • Screening models were built using image features, age, sex, and BMI, with performance evaluated.

Main Results:

  • The best model achieved an ROC-AUC of 0.877 and PR-AUC of 0.838.
  • Sensitivity and specificity were 87.50% and 76.67%, respectively.
  • A model using only image features showed strong performance (ROC-AUC 0.814, PR-AUC 0.726).

Conclusions:

  • Image recognition of neck appearance provides a highly predictive screening tool for sarcopenic dysphagia.
  • The developed screening test demonstrates significant potential for early detection.
  • This method offers a simple and low-risk approach to identify individuals with sarcopenic dysphagia.