ABSTRACT
Objective:To evaluate endoscopic retrograde appendicitis therapy in treatment of children with acute uncomplicated appendicitis.Methods:Sixty children patients were admitted at the Affiliated Hospital of Zhengzhou University from Oct 2019 to Jun 2021 and were divided into ERAT group ( n=30) and LA group ( n=30). Results:All operations were successfully performed . ERAT children started oral feeding earlier [(6.8±2.0) h vs. (12.3±2.0) h, t=-10.636, P<0.001], postoperative hospital stay was shorter [(3.2±1.3) d vs. (5.0±1.3) d, t=-5.360, P<0.001]. After 14 months follow up, the recurrence rate in the ERAT group was 6%. The complication rate of LA was 10%. Conclusion:ERAT is a safe and effective therapy in treating children with acute uncomplicated appendicitis with low,acceptable recurrence rate.
ABSTRACT
@#With the widespread use of Internet, the amount of data in the field of traditional Chinese medicine (TCM) is growing exponentially. Consequently, there is much attention on the collection of useful knowledge as well as its effective organization and expression. Knowledge graphs have thus emerged, and knowledge reasoning based on this tool has become one of the hot spots of research. This paper first presents a brief introduction to the development of knowledge graphs and knowledge reasoning, and explores the significance of knowledge reasoning. Secondly, the mainstream knowledge reasoning methods, including knowledge reasoning based on traditional rules, knowledge reasoning based on distributed feature representation, and knowledge reasoning based on neural networks are introduced. Then, using stroke as an example, the knowledge reasoning methods are expounded, the principles and characteristics of commonly used knowledge reasoning methods are summarized, and the research and applications of knowledge reasoning techniques in TCM in recent years are sorted out. Finally, we summarize the problems faced in the development of knowledge reasoning in TCM, and put forward the importance of constructing a knowledge reasoning model suitable for the field of TCM.