Related Experiment Video
Updated: Jun 10, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Student Pharmacists' Perceptions of Artificial Intelligence and Machine Learning in Pharmacy Practice and Pharmacy
Xiangjun Zhang1, Chi Chun Steve Tsang1, Destiny D Ford1
1University of Tennessee Health Science Center College of Pharmacy, Department of Clinical Pharmacy & Translational Science, Memphis, TN, USA.
Objective:
This study explored student pharmacists' perceptions and attitudes regarding artificial intelligence (AI) and machine learning (ML) in pharmacy practice. Due to AI/ML's promising prospects, understanding students' current awareness, comprehension, and hopes for their use in this field is essential.
Methods:
In April 2024, a Zoom focus group discussion was conducted with 6 student pharmacists using a self-developed interview guide. The guide included questions about the benefits, challenges, and ethical considerations of implementing AI/ML in pharmacy practice and education. The participants' demographic information was collected through a questionnaire. The research team conducted a thematic analysis of the discussion transcript. The results generated by a team member using NVivo were compared with those generated by ChatGPT, and all discrepancies were addressed.
Results:
Student pharmacists displayed a generally positive attitude toward the implementation of AI/ML in pharmacy practice but lacked knowledge about AI/ML applications. Participants recognized several advantages of AI/ML implementation in pharmacy practice, including improved accuracy and time-saving for pharmacists. Some identified challenges were alert fatigue, AI/ML-generated errors, and the potential obstacle to person-centered care. The study participants expressed their interest in learning about AI/ML and their desire to integrate these technologies into pharmacy education.
Conclusion:
The demand for integrating AI/ML into pharmacy practice is increasing. Student and professional pharmacists need additional AI/ML training to equip them with knowledge and practical skills. Collaboration between pharmacists, institutions, and AI/ML companies is essential to address barriers and advance AI/ML implementation in the pharmacy field.
More Related Videos
05:49Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
Published on: February 23, 2024
04:09Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
Published on: October 10, 2018
Related Concept Videos
Issues And Trends In Healthcare Delivery System
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
Current Trends in Nursing II
Biopharmaceutics and Pharmacokinetics: Overview
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
Introduction to Cognitive Psychology
This field emerged in the mid-20th century, following a period dominated by behaviorism, which...
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...