Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Artificial Intelligence in Community Pharmacy
0
Zitationen
5
Autoren
2023
Jahr
Abstract
Artificial Intelligence (AI) has a more pivotal role in healthcare. Pharmacies and pharmacists will be equipped and empowered with these tools and technologies to assist local communities in expanding their capabilities and responsibilities. Pharmacies and pharmacists have played an unprecedented role in two of the great crises of the 21st century: the opioid epidemic and the COVID-19 pandemic. Necessity breeds innovation, and pharmacies, which often are open 24/7, operate in local communities (the vast majority of people in the United States live within 5 miles of their nearest pharmacy). As of August 2022, pharmacies have delivered 263.3 million doses of COVID-19 vaccines and received regulatory permission to dispense Narcan Opens a new window (in the context of the opioid epidemic) and Paxlovid Opens a new window (in the context of the COVID-19 pandemic), proving their effectiveness in immediate patient care. Pharmacists have closer relationships with the patient than most providers and are well-positioned to play an expanded role in medication reconciliation, adherence programs, and even prescribing medicine. Recently, several programs focusing on drug therapy have been described. They guide drug interactions, drug therapy monitoring, and drug formulary selection. There are many aspects of pharmacy that AI can have an impact on and the reader is challenged to consider these possibilities because they may someday become a reality in pharmacy. The purpose of this chapter is to create awareness for AI as a component of pharmacy in the future, to encourage pharmacists to embrace this advancement, and, as much as possible, put in effort to acquire the relevant skills, which will enable us to contribute toward the much-envisaged development.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.260 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.116 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.493 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.438 Zit.