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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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Demystifying artificial intelligence in pharmacy.

Scott D Nelson1, Colin G Walsh2, Casey A Olsen3

  • 1Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN.

American Journal of Health-System Pharmacy : AJHP : Official Journal of the American Society of Health-System Pharmacists
|July 5, 2020
PubMed
Summary
This summary is machine-generated.

This primer explains artificial intelligence (AI) for pharmacists, focusing on its use in medication management. Understanding AI principles and applications is crucial for improving patient care through collaboration.

Keywords:
artificial intelligencemachine learningmedical decision makingmedication systemsneural networksprediction

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Area of Science:

  • Informatics
  • Computer Science
  • Clinical Pharmacy

Background:

  • Artificial intelligence (AI) involves computer systems performing human-like cognitive tasks.
  • Augmented intelligence emphasizes collaboration between computers and clinicians for better patient outcomes.
  • Understanding AI terminology facilitates effective communication between clinicians and data scientists.

Purpose of the Study:

  • To equip pharmacists and clinicians with foundational knowledge of AI principles.
  • To explain the practical applications of AI within the medication-use process.
  • To guide the identification of suitable problems for AI implementation in healthcare.

Main Methods:

  • Discussion of AI concepts and terminology.
  • Explanation of AI model lifecycle: training, validation, implementation, evaluation, and maintenance.
  • Exploration of AI's limitations in the medication-use process.

Main Results:

  • Provides a framework for understanding and applying AI in pharmacy practice.
  • Highlights the importance of clinician-data scientist collaboration.
  • Identifies potential benefits and limitations of AI in medication management.

Conclusions:

  • Pharmacists are essential in developing and evaluating healthcare AI.
  • Core AI concepts are necessary for pharmacists to critically assess AI's role in patient care.
  • AI understanding supports the evolution of clinical practice and enhanced patient outcomes.