Abstract
Nowadays, there are thousands of approved drugs that can be used for treating people who have medical problems. Therefore, drug warnings and precautions are denoted to recognize a discrete set of adverse effects and other implied protection uncertainties that are useful for patient control. Methods/analysis/findings: In this study, the intended framework is divided into two principal stages: data retrieval and data processing. Firstly, in the data collection stage, drug reports, drug interactions, malfunctions, number of deaths, and other factors had been obtained from various references, including RxNorm and Drug Bank using web service. Secondly, in the data processing phase, different data mining algorithms used to classify drugs into suitable drugs and non-suitable drugs. Application/improvements: According to the experimental results, we found that the decision tree has more accuracy (97.9%) than other state-of-art methods.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Proceeding International Conference on Science and Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
