Diagnostic value of a deep learning-based hyoid bone tracking model for aspiration in patients with post-stroke dysphagia.
Yeong Hwan RyuJi Hyun KimDohhyung KimSeo Young KimSeong Jae LeePublished in: Digital health (2024)
Hyoid bone movement of PSD patients can be measured quantitatively and efficiently using a deep learning model. Deep learning model-based analysis of hyoid bone movement seems to be useful for predicting aspiration risk and the possibility of resuming oral feeding.
Keyphrases
- deep learning
- bone mineral density
- end stage renal disease
- convolutional neural network
- artificial intelligence
- bone loss
- soft tissue
- machine learning
- ejection fraction
- bone regeneration
- newly diagnosed
- chronic kidney disease
- ultrasound guided
- postmenopausal women
- peritoneal dialysis
- body composition
- patient reported outcomes
- breast cancer risk