Prospects of 3D Printing Technology in Dental Medicine

With the continuous advancement of technology,the application of 3D printing technology in the field of dental medicine is becoming increasingly widespread.This article aims to explore the current applications and future potential of 3D printing technology in dental medicine and to analyze its benefits and challenges.It first introduces the current state of 3D printing technology in dental implants,crowns,bridges,orthodontics,and maxillofacial surgery.It then discusses the potential applications of 3D printing technology in oral tissue engineering,drug delivery systems,personalized dental prosthetics,and surgical planning.Finally,it analyzes the benefits of 3D printing technology in dental medicine,such as improving treatment accuracy and patient comfort,and shortening treatment times,while also highlighting the challenges faced,such as costs,material choices,and technical limitations.This article aims to provide a reference for professionals in the field of dental medicine and to promote the further application and development of 3D printing technology in this area.

Artificial intelligence in dentistry:Harnessing big data to predict oral cancer survival

BACKGROUND Oral cancer is the sixth most prevalent cancer worldwide.Public knowledge in oral cancer risk factors and survival is limited.AIM To come up with machine learning(ML)algorithms to predict the length of survival for individuals diagnosed with oral cancer,and to explore the most important factors that were responsible for shortening or lengthening oral cancer survival.METHODS We used the Surveillance,Epidemiology,and End Results database from the years 1975 to 2016 that consisted of a total of 257880 cases and 94 variables.Four ML techniques in the area of artificial intelligence were applied for model training and validation.Model accuracy was evaluated using mean absolute error(MAE),mean squared error(MSE),root mean squared error(RMSE),R2 and adjusted R2.RESULTS The most important factors predictive of oral cancer survival time were age at diagnosis,primary cancer site,tumor size and year of diagnosis.Year of diagnosis referred to the year when the tumor was first diagnosed,implying that individuals with tumors that were diagnosed in the modern era tend to have longer survival than those diagnosed in the past.The extreme gradient boosting ML algorithms showed the best performance,with the MAE equaled to 13.55,MSE 486.55 and RMSE 22.06.CONCLUSION Using artificial intelligence,we developed a tool that can be used for oral cancer survival prediction and for medical-decision making.The finding relating to the year of diagnosis represented an important new discovery in the literature.The results of this study have implications for cancer prevention and education for the public.

Current status and future prospects of stomatology research

Research in stomatology(dental medicine)continues to expand globally and is oriented towards solving clinical issues,focusing on clarifying the clinical relevance and potential mechanisms of oral–systemic connections via clinical epidemiology,oral microecological characterization,and the establishment of animal models.Interdisciplinary integration of materials science and tissue engineering with stomatology is expected to lead to the creation of innovative materials and technologies to better resolve the most prevalent and challenging clinical issues such as peri-implantitis,soft and hard tissue defects,and dentin hypersensitivity.With the rapid development of artificial intelligence(AI),5th generation mobile communication technology(5G),and big data applications,“intelligent stomatology”is emerging to build models for better clinical diagnosis and management,accelerate the reform of education,and support the growth and advancement of scientific research.Here,we summarized the current research status,and listed the future prospects and limitations of these three aspects,aiming to provide a basis for more accurate etiological exploration,novel treatment methods,and abundant big data analysis in stomatology to promote the translation of research achievements into practical applications for both clinicians and the public.