Demystifying artificial intelligence in pharmacy
- 4 July 2020
- journal article
- research article
- Published by Oxford University Press (OUP) in American Journal of Health-System Pharmacy
- Vol. 77 (19) , 1556-1570
Abstract
Purpose: To provide pharmacists and other clinicians with a basic understanding of the underlying principles and practical applications of artificial intelligence (AI) in the medication-use process.Summary: “Artificial intelligence” is a general term used to describe the theory and development of computer systems to perform tasks that normally would require human cognition, such as perception, language understanding, reasoning, learning, planning, and problem solving. Following the fundamental theorem of informatics, a better term for AI would be “augmented intelligence,” or leveraging the strengths of computers and the strengths of clinicians together to obtain improved outcomes for patients. Understanding the vocabulary of and methods used in AI will help clinicians productively communicate with data scientists to collaborate on developing models that augment patient care. This primer includes discussion of approaches to identifying problems in practice that could benefit from application of AI and those that would not, as well as methods of training, validating, implementing, evaluating, and maintaining AI models. Some key limitations of AI related to the medication-use process are also discussed.Conclusion: As medication-use domain experts, pharmacists play a key role in developing and evaluating AI in healthcare. An understanding of the core concepts of AI is necessary to engage in collaboration with data scientists and critically evaluating its place in patient care, especially as clinical practice continues to evolve and develop.Keywords
This publication has 81 references indexed in Scilit:
- Computational Phenotype Discovery Using Unsupervised Feature Learning over Noisy, Sparse, and Irregular Clinical DataPLOS ONE, 2013
- Derivation and validation of an index to predict early death or unplanned readmission after discharge from hospital to the communityCanadian Medical Association Journal, 2010
- The coming of age of artificial intelligence in medicineArtificial Intelligence in Medicine, 2009
- A "Fundamental Theorem" of Biomedical InformaticsJournal of the American Medical Informatics Association, 2009
- General Cardiovascular Risk Profile for Use in Primary CareCirculation, 2008
- A Risk Score to Predict In-Hospital Mortality for Percutaneous Coronary InterventionsJACC, 2006
- The use of receiver operating characteristic curves in biomedical informaticsJournal of Biomedical Informatics, 2005
- Users' Guides to the Medical LiteratureJAMA, 1994
- Internist-I, an Experimental Computer-Based Diagnostic Consultant for General Internal MedicineNew England Journal of Medicine, 1982
- Precursors of sudden coronary death. Factors related to the incidence of sudden death.Circulation, 1975