BACKGROUND: Cardiometabolic disorders pose significant health risks globally. Metabolic syndrome, characterized by a cluster of potentially reversible metabolic abnormalities, is a known risk factor for these disorders. Early detection and interventi...
BACKGROUND: Advanced unresectable gastric cancer (GC) patients were previously treated with chemotherapy alone as the first-line therapy. However, with the Food and Drug Administration's (FDA) 2022 approval of programmed cell death protein 1 (PD-1) i...
OBJECTIVE: The purpose of this study is to explore the perspectives, familiarity, and readiness of dental faculty members regarding the integration and application of artificial intelligence (AI) in dentistry, with a focus on the possible effects on ...
A popular and widely suggested measure for assessing unilateral hand motor skills in stroke patients is the box and block test (BBT). Our study aimed to create an augmented reality enhanced version of the BBT (AR-BBT) and evaluate its correlation to ...
Within the medical field of human assisted reproductive technology, a method for interpretable, non-invasive, and objective oocyte evaluation is lacking. To address this clinical gap, a workflow utilizing machine learning techniques has been develope...
Human instructors fluidly communicate with hand gestures, head and body movements, and facial expressions, but robots rarely leverage these complementary cues. A minimally supervised social robot with such skills could help people exercise and learn ...
OBJECTIVE: One of the main causes of death worldwide among young people are car crashes, and most of these fatalities occur to children who are seated in the front passenger seat and who, at the time of an accident, receive a direct impact from the a...
INTRODUCTION: An ideal orthodontic treatment involves qualitative and quantitative measurements of dental and skeletal components to evaluate patients' discrepancies, such as facial, occlusal, and functional characteristics. Deciding between orthodon...
Journal of stomatology, oral and maxillofacial surgery
May 7, 2024
This study aimed to assess the diagnostic performance of a machine learning approach that utilized radiomic features extracted from Cone Beam Computer Tomography (CBCT) images and inflammatory biomarkers for distinguishing between Dentigerous Cysts (...
In this study, our objective was to assess the performance of two deep learning-based hippocampal segmentation methods, SynthSeg and TigerBx, which are readily available to the public. We contrasted their performance with that of two established tech...
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