Publications by authors named "H Chew"
Objective: This randomized controlled trial compared the 1-year clinical efficacy of Scotchbond Universal Adhesive Plus (SBU+) with that of its predecessor Scotchbond Universal Adhesive (SBU) to restore Class I and Class II preparations using the self-etch strategy in adult patients.
Materials And Methods: Fifty-one subjects participated in this study. Two posterior teeth in each subject were randomized to a restoration with SBU+ or to a restoration with SBU (control) using the self-etch strategy.
There is a new awareness of the widespread nature of metabolic dysfunction-associated steatotic liver disease (MASLD) and its connection to cardiovascular disease (CVD). This has catalyzed collaboration between cardiologists, hepatologists, endocrinologists, and the wider multidisciplinary team to address the need for earlier identification of those with MASLD who are at increased risk for CVD. The overlap in the pathophysiologic processes and parallel prevalence of CVD, metabolic syndrome, and MASLD highlight the multisystem consequences of poor cardiovascular-liver-metabolic health.
View Article and Find Full Text PDFBackground: During the COVID-19 pandemic, governments across the world implemented processes and policies to limit the spread of COVID-19, especially in long-term care (LTC) homes. This led to changes in technology use for persons living in LTC homes, their families and friends, as well as the paid workforce dedicated to caring for them.
Objective: The study describes the role of technology and its impact on the experiences of LTC staff working in northern and rural areas in Western Canada during COVID-19.
Purpose: To demonstrate that high-seed, ultra-high-resolution spectral-domain optical coherence tomography (SD-OCT) technology can image in vivo fine morphological features in the healthy and pathological human limbus.
Methods: A compact, fiberoptic SD-OCT system was developed for imaging the human limbus. It combines ∼1.
Article Synopsis
- - The text discusses the limitations of current blood glucose monitoring methods, which are invasive and uncomfortable, and highlights the potential benefits of noninvasive blood glucose monitoring that utilizes artificial intelligence (AI).
- - A systematic review analyzed 33 studies from various regions, focusing on the use of different noninvasive techniques such as optical methods, electrochemical sensors, and machine learning models for blood glucose estimation.
- - Results showed accuracy in glucose estimation varied significantly, with the most commonly used AI algorithms being random forest and artificial neural networks, indicating a growing interest in improving noninvasive monitoring technologies.