Recent reports of multivariate machine learning (ML) techniques have highlighted their potential use to detect prognostic and diagnostic markers of pain. However, applications to date have focussed on acute experimental nociceptive stimuli rather tha...
American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics
26718386
INTRODUCTION: The decision to extract teeth for orthodontic treatment is important and difficult because it tends to be based on the practitioner's experiences. The purposes of this study were to construct an artificial intelligence expert system for...
INTRODUCTION: The aim of this study was to build and validate five types of machine learning models that can predict the occurrence of BRONJ associated with dental extraction in patients taking bisphosphonates for the management of osteoporosis.
Patients' postoperative facial swelling following third molars extraction may have both biological impacts and social impacts. The purpose of this study was to evaluate the accuracy of artificial neural networks in the prediction of the postoperative...
The approximity of the inferior alveolar nerve (IAN) to the roots of lower third molars (M3) is a risk factor for the occurrence of nerve damage and subsequent sensory disturbances of the lower lip and chin following the removal of third molars. To a...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
33019046
A measurement setup is proposed that, for the first time, is capable of capturing the combination of high forces and subtle movements exerted during tooth removal procedures in high detail and in a reproducible manner by using robot technology. The o...
This paper proposes a convolutional neural network (CNN)-based deep learning model for predicting the difficulty of extracting a mandibular third molar using a panoramic radiographic image. The applied dataset includes a total of 1053 mandibular thir...
OBJECTIVE: To examine the robustness of the published machine learning models in the prediction of extraction vs non-extraction for a diverse US sample population seen by multiple providers.