Big Data Analysis And Visualization Of Medical Testing

In recent years,the development of big data,cloud computing,’Internet+’,artificial intelligence and other technologies has accelerated the improvement of the informatization level of the traditional medical industry.A large amount of diversified medical and health data provides the foundation for precision medical services based on big data.Clinical urine routine is an indispensable and important means of disease screening,which can provide objective and accurate information for the examination and treatment of various clinical diseases.Medical test data embodies the disease status and disease change trend.How to fully tap the value of laboratory data and present the data effectively provides objective and accurate information for the diagnosis and treatment of clinical diseases.It has important practical significance.In this theies,the disease prediction method and data mining analysis are implemented based on urine detection index data,weather factors’impact on the disease is analyzed and the data is visualized,providing an auxiliary diagnosis and treatment method for disease diagnosis.The main content and research results are as follows.(1)The disease prediction analysis method is analyzed based on the urine test data of XGboost.First,17427 urine test samples were pretreated,and secondly,the types of diseases were divided into multiple types,four types and two types for disease prediction.Finally,after the parameters are adjusted,better prediction accuracy is obtained when there are fewer disease types(2)The analysis of disease association is performed based on the FP-growth algorithm.In order to explore the relationship between urine test indicators and disease,in this theies,the impact of weather on the disease was analyzed based on the FP-growth algorithm;bronchial pneumonia samples 11 urine indicators,weather factors and disease were analyzed.The correlation between the final urine test index and the disease and the influence of climate on the disease were obtained separately.(3)The algorithm is implemented and the data is visualized.The theies’s disease prediction analysis algorithm and data association analysis algorithm are implemented based on urine detection data sets.To meet the needs of visual display of medical test data trends and dimensions,urine test data and diseases are displayed and interacted in multiple angles,multiple views,and multiple dimensions.