Information Extraction and Recognition Algorithm of Test Sheet in Veterinary Laboratory

Abstract

With the development of medical technology, veterinary clinical trials are increasingly used in disease diagnosis, prevention and treatment. Animal testing is a science that can be directly observed under routine conditions without human intervention. It has the characteristics of randomness, strong accuracy and objectivity. Therefore, in order to ensure the correctness of the test information, it must be strictly controlled; on the other hand, it is necessary to ensure that the test results are correct before the final valid data information can be obtained. Since every information category on the Internet has a large amount of data, collecting information on the Internet, extracting necessary information, and analyzing and recommending based on user behavior will have a huge impact on the online market. At the same time, information extraction technology can be widely used in various fields, but current applications and implementations are mainly concentrated in specific fields. How to extract information more quickly and accurately and improve the quality and performance of extraction is also a hot and difficult point. In order to increase the awareness of relevant departments on the importance of laboratory testing and testing, strengthen the construction of veterinary drug laboratories. This article adopts experimental analysis and data analysis methods, and aims to use the advantages of information extraction and recognition algorithms to extract effective data from veterinary laboratory test reports more accurately and efficiently, and to improve the quality and performance of information extraction. According to the research results, under the test template, the extraction speed of the test sheet to be tested is faster, and the extraction accuracy is higher than the recognition accuracy, and the recognition ability needs to be further improved.