1.The Distributed Naive Bayesian Intelligent Diagnosis System Based on Hadoop
Yingzi LIN ; Yuping ZENG ; Feilong XU ; Haoyang FU
Journal of Medical Informatics 2015;(7):53-57
The paper introduces the research idea, design and realization of the distributed Naive Bayesian intelligent diagnosis sys-tem based on Hadoop, makes optimization and improvement according to its application in Traditional Chinese Medicine ( TCM) Hospital of Guangdong Province, including algorithm design improvement and enhancement of accuracy, extensibility and security of the system.
2.Building a control framework for hospital medical quality control
Lan CHENG ; Weirong WANG ; Jun LI ; Rongyuan YANG ; Yingzi LIN ; Haoyang FU ; Xiaoying DOU
Chinese Journal of Hospital Administration 2012;28(4):289-292
Data mining technology is called into play to comb and excavate data in the hospital information system(HIS)for the purposes of hospital management and patient safety.Data tables in the electronic medical record system were effectively remodeled as necessary.These measures help build a medical quality surveillance system which is based on the electronic medical record system,with such functions as real-time monitoring and pre-warning.The control framework consists the critical cases control system,surgery and invasive operation control system,overall control system,and TCM strengths application control system.
3.Influence of different processing motivation on the intergroup interaction willingness of college students
Yatong LI ; Haoyang BAI ; Xiaolong FU ; Xiaobin DING
Chinese Journal of Behavioral Medicine and Brain Science 2023;32(4):334-340
Objective:To explore the effect and mechanism of different processing motivation on college students' intergroup interaction willingness by technology of eye movement.Methods:Sixty college students conforming to the study conditions were selected from Northwest Normal University and randomly divided into ingroup motivation group ( n=30) and outgroup motivation group ( n=30) according to the random number table method. Subjects of the two groups first participated in the eye movement task, and then participated in the partner selection task.In the eye movement task, the percentage of time that subjects looked at faces of different groups was recorded.And in the partner selection task, the number of selections that subjects selected faces from different groups was recorded.SPSS 20.0 software was used for repeated measurement analysis of variance. Results:(1) In the eye movement task, there was a significant interaction of group and face group type ( F=13.37, P<0.001), but the main effects of group( F=3.23, P=0.077), and face group type ( F=0.09, P>0.05) were not significant. Further simple effect analysis showed that the percentage of time that the ingroup motors looked at the yellow race((16.00±0.06)%) was significantly higher than that of the outgroup motors ((12.00±0.04)%), and the percentage of time that the outgroup motors looked at the white race((17.00±0.06)%) was significantly higher than that of the ingroup motors ((9.00±0.04)%). (2) In the task of partner selection, there was a significant interaction among group, face group type and face old and new types( F=4.38, P=0.041), and the main effect of face group type was significant( F=14.87, P<0.001). The main effect of old and new types of face was significant( F=8.88, P=0.004), but the main effect of group was not significant ( P>0.05). Further simple effect analysis showed that the two groups of college students had statistically significant differences in the selection times of familiar faces from different groups( F=11.51, P=0.001). The number of times that the ingroup generator (5.51±1.14) selected the familiar yellow race as its partner was significantly greater than that of the outgroup generator (2.30±0.65). The number of times that the outgroup generator (5.40±1.00) selected the familiar white race as its partner was significantly greater than that of the ingroup generator (3.47±0.94). (3)Preferential attention to the ingroup members was a mediator between processing motivation and intergroup interaction willingness (mediating effect=0.20, 95% CI=0.02-0.31). Conclusion:Ingroup processing motivation has a threatening effect on college students' intergroup interaction willingness, outgroup processing motivation has a promoting effect on college students' intergroup interaction willingness, and processing motivation affects intergroup interaction willingness through ingroup bias.
4.Design and Implementation of the Scientific Data Management Platform of Traditional Chinese Medicine
Feilong XU ; Jia LYU ; Jiarong WU ; Yuping ZENG ; Haoyang FU
Journal of Medical Informatics 2023;44(12):78-82
Purpose/Significance To address the challenge of low willingness to share scientific data among stakeholders in the tradi-tional Chinese medicine(TCM)industry,and to promote standardization,aggregation,sharing,and application of scientific data in the field of TCM.Method/Process By adhering to national standards for scientific data submission and management,integrating technologies such as blockchain and digital watermarking,the study aims to establish atrusted process for the exchange of scientific data in the field of TCM and build a TCM scientific data management platform.Result/Conclusion This platform will provide information technology support for regional TCM scientific data exchange,and effectively improve the efficiency and willingness of scientific data exchange within the region.