Supporting Prescriptions with Synonym Matching of Section Names in Prospectuses

摘要

The field of medicine still reports errors because of insufficient knowledge or resources, work load or data not available at the right time and place, and this may be fatal for a patient. To improve the healthcare quality, a doctor needs accurate and complex information processing when accessing drug information. Our work builds on improvement of accessing drug information for a better treatment through homogenization of sections in a prospectus. The sections names in a prospectus may be different for one source to another, and in this article, we propose a method to homogenize the content of all drug prospectuses. Once a correct homogenization of the sections has been established, the prospectuses can be used in clinical decision applications to provide the necessary data for physicians. Classification of the section names is using the Cousine similarity method and the Scikit-leam machine learning software. The best results were obtained with the Scikit-learn software.