Expert consensus on precise diagnosis and treatment of hilar cholangiocarcinoma guided by three-dimensional visualization technology

AbstractCold injury refers to local or systemic injury caused by a rapid, massive loss of body heat in a cold environment. The incidence of cold injury is high. However, the current situation regarding the diagnosis and treatment of cold injury in our country is not ideal. To standardize and improve the level of clinical diagnosis and treatment of cold injury in China, it is necessary to make a consensus that is practical and adapted to the conditions in China. We used the latest population-level epidemiological and clinical research data, combined with relevant literature from China and foreign countries. The consensus was developed by a joint committee of multidisciplinary experts. This expert consensus addresses the epidemiology, diagnosis, on-site emergency procedures, in-hospital treatment, and prevention of cold injury.

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Research on the university intelligent learning analysis system based on AI

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189820 ◽

2021 ◽

pp. 1-10

Author(s):

Meng Huang ◽

Shuai Liu ◽

Yahao Zhang ◽

Kewei Cui ◽

Yana Wen

Keyword(s):

Artificial Intelligence ◽

Big Data ◽

Academic Performance ◽

Clustering Algorithm ◽

Back Propagation ◽

Three Dimensional ◽

Training Model ◽

Future Trend ◽

Artificial Intelligence Technology ◽

Visualization Technology

The integration of Artificial Intelligence technology and school education had become a future trend, and became an important driving force for the development of education. With the advent of the era of big data, although the relationship between students’ learning status data was closer to nonlinear relationship, combined with the application analysis of artificial intelligence technology, it could be found that students’ living habits were closely related to their academic performance. In this paper, through the investigation and analysis of the living habits and learning conditions of more than 2000 students in the past 10 grades in Information College of Institute of Disaster Prevention, we used the hierarchical clustering algorithm to classify the nearly 180000 records collected, and used the big data visualization technology of Echarts + iView + GIS and the JavaScript development method to dynamically display the students’ life track and learning information based on the map, then apply Three Dimensional ArcGIS for JS API technology showed the network infrastructure of the campus. Finally, a training model was established based on the historical learning achievements, life trajectory, graduates’ salary, school infrastructure and other information combined with the artificial intelligence Back Propagation neural network algorithm. Through the analysis of the training resulted, it was found that the students’ academic performance was related to the reasonable laboratory study time, dormitory stay time, physical exercise time and social entertainment time. Finally, the system could intelligently predict students’ academic performance and give reasonable suggestions according to the established prediction model. The realization of this project could provide technical support for university educators.

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