Digital dentistry has witnessed significant advancements in recent years, driven by extensive research following the introduction of cutting-edge technologies such as CAD/CAM and 3D oral scanners. Until now, 2D images obtained via x-ray or CT scans were critical to detect anomalies and for decision-making. This review describes the main principles and applications of supervised, unsupervised, and reinforcement learning in medical applications. In this context, we present a diverse range of artificial intelligence networks with potential applications in dentistry, accompanied by existing results in the field.

BACKGROUND: The prevalence of hyperuricemia has increased over the past few decades. Hyperuricemia is responsible for the increased risk of hypertension, type 2 diabetes mellitus, chronic renal disease, and cardiovascular disease. Health-related quality of life (HQoL) has been increasingly used as an outcome in clinical trials, effectiveness research, and research on quality of care. Therefore, we aimed to analyze the association between hyperuricemia and HQoL in Korean adults aged >19 years.METHODS: We included 2,376 male and 2,593 female who participated in the Korea National Health and Nutrition Examination Survey from 2016 to 2017. Hyperuricemia was defined as a serum uric acid (SUA) level of 7 mg/dL. The Euro quality of life-5 dimension (EQ-5D) questionnaire was used to measure HQoL. A multiple logistic regression analysis was performed to examine the association between hyperuricemia and HQoL.RESULTS: The EQ-5D index score of the hyperuricemia group was significantly lower than of the healthy group. After adjusting for multiple covariates, the odds ratio (95% confidence interval, [CI]) for mobility issues was 1.46 (95% CI, 1.211–1.683) in male and 1.33 (95% CI, 0.716–2.464) in female; however, the difference was not statistically significant for female.CONCLUSION: Hyperuricemia was associated with reduced quality of life. It is important to control SUA levels to improve HQoL.
Adult ; Cardiovascular Diseases ; Diabetes Mellitus, Type 2 ; Female ; Humans ; Hypertension ; Hyperuricemia ; Korea ; Logistic Models ; Male ; Nutrition Surveys ; Odds Ratio ; Prevalence ; Quality of Life ; Renal Insufficiency, Chronic ; Uric Acid