Artificial intelligence in pharmacy predicting adverse drug reactions

• Autores: Moamen Abdelfadil Ismail, Shahad Mari Alshahrani, Mohammad Ali A 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, Naif Abdulrahman Y. Alfaifi
• Localización: Revista iberoamericana de psicología del ejercicio y el deporte, ISSN 1886-8576, Vol. 20, Nº. 6, 2025, págs. 572-578
• Idioma: inglés
• Enlaces
  • Texto completo (pdf)
• Referencias bibliográficas
  • 1. Mohsen A., Tripathi L.P., Mizuguchi K. Deep learning prediction of adverse drug reactions in drug discovery using open TG–GATEs and FAERS...
  • 2. Yalçın N., Kaşıkcı M., Çelik H.T., et al. An artificial intelligence approach to support detection of neonatal adverse drug reactions...
  • 3. Takase T., Masumoto N., Shibatani N., et al. Evaluating the safety and efficiency of robotic dispensing systems. J Pharm Health Care Sci....
  • 4. Jungreithmayr V., Meid A.D., Haefeli W.E., Seidling H.M. The impact of a computerized physician order entry system implementation on 20...
  • 5. Blasiak Agata, Truong Anh, Jeit Wen, et al. PRECISE CURATE.AI: A prospective feasibility trial to dynamically modulate personalized chemotherapy...
  • 6. Wang Z., Ong C.L., Fu Z. AI models to assist vancomycin dosage titration. Front Pharmacol. 2022 Feb 8; 13:801928. doi: 10.3389/fphar.2022.801928.
  • 7. Roche-Lima A., Roman-Santiago A., Feliu-Maldonado R., et al. Machine learning algorithm for predicting warfarin dose in caribbean hispanics...
  • 8. Mei S., Zhang K. A machine learning framework for predicting drug–drug interactions. Sci Rep. 2021 Sep 2;11(1):17619. doi: 10.1038/s41598-021-...
  • 9. Van Laere S., Muylle K.M., Dupont A.G., Cornu P. Machine learning techniques outperform conventional statistical methods in the prediction...
  • 10. Balestra M., Chen J., Iturrate E., Aphinyanaphongs Y., Nov O. Predicting inpatient pharmacy order interventions using provider action...
  • 11. Xingwei W., Huan C., Mengting L., et al. A machine learning-based risk warning platform for potentially inappropriate prescriptions for...
  • 12. Tai C.-T., Sue K.-L., Hu Y.-H. Machine learning in high-alert medication treatment: a study on the cardiovascular drug. Appl Sci. 2020;10(17):5798.
  • 13. Wongyikul P., Thongyot N., Tantrakoolcharoen P., Seephueng P., Khumrin P. High alert drugs screening using gradient boosting classifier....
  • 14. Patel J., Ladani A., Sambamoorthi N., et al. A machine learning approach to identify predictors of potentially inappropriate non-steroidal...
  • 15. Nagata K., Tsuji T., Suetsugu K., et al. Detection of overdose and underdose prescriptions—an unsupervised machine learning approach....
  • 16. Yalçın N., Kaşıkcı M., Çelik H.T., et al. Development and validation of a machine learning-based detection system to improve precision...
  • 17. Corny J., Rajkumar A., Martin O., et al. A machine learning-based clinical decision support system to identify prescriptions with a high...
  • 18. Kessler S., Desai M., McConnell W., et al. Economic and utilization outcomes of medication management at a large Medicaid plan with disease...
  • 19. Bu F., Sun H., Li L., et al. Artificial intelligence-based internet hospital pharmacy services in China: Perspective based on a case study....