In recent years,artificial intelligence(AI),such as image recognition and fixed-point and digital scan-ning,has been increasingly applied in dental orthodontics.ChatGPT is an emerging artificial intelligence technology that has attracted a considerable amount of attention from people of all walks of life since its introduction.This paper discusses the application potential of ChatGPT in the field of orthodontics from two perspectives—education and clini-cal practice—and analyzes its limitations.Current reports show that ChatGPT can improve the efficiency of teaching in orthodontic education as well as assist users in completing medical mock exams training,writing papers and conducting academic research,etc.In the clinic,ChatGPT can be used to engage patients in medical dialog,simplify clinical proce-dures and improve diagnostic and treatment efficiency.However,because ChatGPT is still in the early stages of research and application,there are problems such as insufficient data,inaccurate answers,and poor academic ethics and privacy.In the future,additional studies,training and optimization are needed to ensure the safety,ethics and benefit of AI,lay-ing the foundation for improving the use of AI in the field of orthodontics.

Objective:To explore the current status of the time to full enteral feeding (FEFt) in very low birth weight infants (VLBWI) and its influencing factors, so as to provide a reference for shortening FEFt and improving infants' prognosis.Methods:This study was a prospective cohort study. Through the Sina-northern Neonatal Network (SNN) , convenience sampling was used to select the data of 158 premature infants with birth weight less than 1 500 g in the Neonatal Intensive Care Unit of a Class Ⅲ Grade A hospital in Shandong Province from January 1, 2019 to December 31, 2020. The current status of FEFt in premature infants was analyzed. According to the median time of FEFt, premature infants were divided into two groups (short FEFt group and long FEFt group) . Single factor χ 2 test or Fisher exact probability, rank sum test and multivariate Logistic regression model were used to analyze the influencing factors of FEFt of VLBWI. Results:This study finally included 145 cases of VLBWI. Multivariate Logistic regression analysis showed that long fasting time, feeding intolerance (FI) , and long positive pressure ventilation treatment time were independent factors of the long FEFt of VLBWI ( P<0.05) , while gestational diabetes was its protective factor ( P<0.05) . FI was related to the fasting time and positive pressure ventilation treatment time, and it was the main reason leading to the long FEFt ( P<0.01) . Hypertension during pregnancy was an independent influencing factor of FI ( P<0.05) . Conclusions:FEFt of VLBWI is still long enough, which is related to long fasting time, long positive pressure ventilation time and FI. FI is the main reason, and hypertension during pregnancy is the root cause of FI. Medical and nursing staff should pay attention to and strengthen the management of VLBWI FI, shorten fasting time and accelerate the rate of milk feeding during positive pressure ventilation treatment, and strengthen the management of hypertension during pregnancy, so as to shorten FEFt in VLBWI and improve the prognosis.