زهرا اوقاني اراني

The safety of medications has become an important issue worldwide due to the increasing number of drugs used in treatment, especially in the elderly population, and the complexity of knowledge regarding drug interactions. This study aimed to discover drug prescribing patterns in cardiac patients and identify drug interactions using data mining algorithms. Pharmaceutical data from 48 hospitalized patients in the cardiology department of Shahid Beheshti Hospital in Kashan were collected and analyzed using knowledge of drug interactions. The Apriori algorithm was employed to extract association rules for identifying drugs that are prescribed simultaneously. After data cleaning and feature selection, 28 severe drug interactions were identified among cardiovascular drugs. The analysis of drug prescribing patterns and drug interactions revealed that cardiovascular and anticoagulant drugs are often prescribed together, indicating a correlation in the treatment of these conditions. Drug interactions with high confidence and low support require special attention. Combinations with high lift indicate potentially dangerous interactions that need to be monitored more closely, while low lift suggests that physicians are aware of the interactions and avoid prescribing them together. Additionally, ICU3 had the highest number of interactions, with 56 interactions, compared to other departments, and the age group of 65 years and older showed the most interactions, with 135 interactions. This study demonstrated that data mining algorithms can accurately identify drug interactions and help improve patient safety. Special attention to elderly patients and busy departments like ICU3 in this hospital can be effective in reducing drug interactions. Furthermore, the use of drug interaction al‎e‎rt systems and consulting with pharmacists before prescribing or consuming medications can be effective in reducing these interactions.

قوانين انجمن , داده كاوي , تداخلات دارويي , بيماري قلبي و عروقي , يادگيري ماشين

Association ruls , data mining , Drug interactions , Cardiovascular disease , machine learning

zahra owqani

Dr. rouzbeh ghousi