Ahmed Bakheet Attiah Al-Malki
Phar.D. Pharmacy Graduate, Saudi Arabia
Publications
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Research Article
Artificial Intelligence In Pharmacy Predicting Adverse Drug Reactions
Author(s): Moamen Abdelfadil Ismail*, Shahad Mari Alshahrani, Abdullah Ali Ibrahim Alshahrani, Ahmed Yahya Hassan Alshehri, Khalid Saeed Abdullah Alshahrani, Ahmed Bakheet Attiah Al-Malki, Abeer Salamah Alsharif, Miral Majed Alsherbi, Jihad Saleh Alrehaili, Mohammed Saeed Aftan, Razan Ahmed Salman Alsharif, Abdullah Mahmoud Bedaiwi, Farah Abdullah Awad Alahmadi, Sumayyah Masoud Dakheel Alrhili and Naif Abdulrahman Y. Alfaifi
Background: Adverse drug reactions (ADRs) are a major cause of morbidity, hospitalizations, and healthcare costs. Traditional pharmacovigilance methods are often limited by underreporting and delays. Artificial intelligence (AI), particularly machine learning (ML) and natural language processing (NLP), offers faster, more accurate ADR detection by integrating diverse data sources such as electronic health records and clinical notes. Methods: A systematic review was conducted following PRISMA guidelines, searching PubMed, Scopus, IEEE Xplore, Web of Science, and Google Scholar for English-language studies published from January 2010 to May 2025. Eligible studies applied AI/ML methods to ADR prediction in pharmacy settings. Two reviewers independently screened and extracted data, with risk of bias assessed using PROBAST. A narrative synthesis .. Read More»