Research on Clinical Characteristics of Metaplastic Chronic Atrophic Gastritis Patients from Complexion Diagnosis Based on Gender Difference / 世界科学技术-中医药现代化

Objective Based on gender differences,this paper discusses the characteristics of facial color diagnosis in male and female patients with metaplastic chronic atrophic gastritis(CAG),and explores the pathological mechanism of different gender patients from the perspective of TCM pathogenesis,so as to provide personalized reference for TCM prevention and treatment of metaplastic CAG.Methods In this study,the complexion information of patients with chronic non atrophic gastritis(CNG)and CAG was collected by MT-BX-01 four-diagnostic instrument.The color colorimetric characteristics of male and female metaplastic CAG patients and CNG patients were analyzed by case-control study.Results In female patients,the L value and a value of liver region in CAG with mild intestinal metaplasia(IM)group,moderate and severe IM were significantly lower than those in CNG group(P<0.05).In male patients,the L value of spleen region in CAG with moderate and severe IM group was significantly higher than that in CNG group(P<0.05).Conclusion There is a certain gender difference in the facial color characteristics of patients with metaplastic CAG.The facial chromaticity value of female patients with metaplastic CAG changes most significantly in the liver area,while that of male patients mainly in the spleen area.It is suggested that the incidence of female metaplastic CAG is mostly related to liver,while that of male is mostly related to spleen,which provides a personalized method for clinical diagnosis and treatment of metaplastic CAG based on gender differences.

Coating matching recommendation based on improved fuzzy comprehensive evaluation and collaborative filtering algorithm.

Coating matching design is one of the important parts of ship coating process design. The selection of coating matching is influenced by various factors such as marine corrosive environment, anti-corrosion period and working conditions. There are also differences in the coating performance requirements for different ship types and different coating parts. At present, the design of coating matching in shipyards depends on the experience of technologist, which is not conducive to the scientific management of ship painting process and the macro control of ship construction cost. Therefore, this paper proposes a hybrid algorithm of fuzzy comprehensive evaluation and collaborative filtering based on user label improvement (IFCE-CF). Based on the analytic hierarchy process (AHP), the evaluation index system of coating matching is constructed, and the weight calculation process of fuzzy comprehensive evaluation is optimized by introducing the user label weight. The collaborative filtering algorithm based on matrix decomposition is used to realize the accurate recommendation of coating matching. Historical coating process data of a shipyard between 2010 and 2020 are selected to verify the recommendation ability of the method in the paper. The results show that using the coating matching intelligent recommendation algorithm proposed in this paper, the root mean square error is < 1.02 and the mean absolute error is < 0.75, the prediction accuracy is significantly better than other research methods, which proves the effectiveness of the method.