Development and Validation of an Ultrasonography-Based Machine Learning Model for Predicting Outcomes of Bruxism Treatments.
Kaan OrhanGokhan YaziciMerve ÖnderCengiz EvliMelek Volkan YaziciMehmet Eray KolsuzNilsun BağışNihan KafaFehmi GönüldaşPublished in: Diagnostics (Basel, Switzerland) (2024)
This study has introduced a machine learning model using SVM analysis on ultrasound (USG) images for bruxism patients, which can detect masseter muscle changes on USG. Support Vector Machine regression analysis showed the combined ML models can also predict the outcome of the pain reduction.
Keyphrases
- machine learning
- deep learning
- end stage renal disease
- magnetic resonance imaging
- newly diagnosed
- chronic kidney disease
- ejection fraction
- artificial intelligence
- chronic pain
- type diabetes
- magnetic resonance
- adipose tissue
- metabolic syndrome
- convolutional neural network
- spinal cord injury
- computed tomography
- optical coherence tomography