Software implementation of Levenshtein distance-based algorithm for automatically generating easily confused drug catalogs
OBJECTIVE To create a highly effective algorithm for automatically generating easily confused drug catalogs(ECDC),as well as to develop a management system for ECDC based on this algorithm,in order to improve the management efficiency of ECDC.METHODS This study,based on Levenshtein distance algorithm,delved deeply into the automatic identification mechanism of easily confused drugs and the screening method for determining similarity thresholds,ultimately leading to the development of an algorithm for automatically generating ECDC.Besides a management system was designed and developed,using SQL Server 2008 R2 Express as the data storage platform and Visual Basic.NET as the programming language.RESULTS The similarity threshold δ played a crucial role in the algorithm for automatically generating ECDC.As the value of δ gradually increased,the total count of easily confused drugs decreased gradually,while the count of drug groups exhibited a pattern of initially increasing and then decreasing.Practically,ECDC could be created using either the generic or varietal names of drugs,with corresponding similarity thresholds of 0.75 and 0.83.Furthermore,ECDC management system had significantly reduced the time required to establish a catalog from about one week to less than one hour,resulting in a substantial enhancement in work efficiency.CONCLUSIONS The algorithm used to automatically generate ECDC is highly efficient and rapid,offering robust technical assistance for the management of easily confused drugs.Implementing the ECDC system can greatly reduce the time cost related to building and maintaining the catalogs,thus significantly improving the efficiency of managing ECDC.
万方数据
维普
