Research in social & administrative pharmacy : RSAP
Feb 12, 2025
INTRODUCTION: Adverse drug reactions (ADRs) significantly impact healthcare systems, leading to increased hospitalization rates and costs. With the growing adoption of artificial intelligence (AI) in healthcare, machine learning (ML) models offer pro...
Research in social & administrative pharmacy : RSAP
Dec 17, 2024
BACKGROUND: Artificial intelligence (AI), a branch of computer science, has been of growing research interest since its introduction to healthcare disciplines in the 1970s. Research has demonstrated that the application of such technologies has allow...
Research in social & administrative pharmacy : RSAP
Nov 5, 2024
BACKGROUND: Pharmacy practice faculty research profiles extend beyond the clinical and social domains, which are core elements of pharmacy practice. But as highlighted by journal editors in the Granada Statements, there is no consensus on these terms...
Research in social & administrative pharmacy : RSAP
Sep 19, 2024
BACKGROUND: Pharmacists are increasingly involved in patient care. Pharmacy practice research helps them identify the most clinically meaningful interventions. However, the lack of a widely accepted controlled vocabulary in this field hinders the dis...
Research in social & administrative pharmacy : RSAP
Apr 10, 2024
OBJECTIVE: Medication management of patients with polypharmacy is highly complex. We aimed to validate a novel Artificial Pharmacology Intelligence (API) algorithm to optimize the medication review process in a comprehensive, personalized, and scalab...
Research in social & administrative pharmacy : RSAP
Jun 4, 2023
Artificial Intelligence (AI) has revolutionized various domains, including education and research. Natural language processing (NLP) techniques and large language models (LLMs) such as GPT-4 and BARD have significantly advanced our comprehension and ...
Research in social & administrative pharmacy : RSAP
Aug 8, 2022
BACKGROUND: The amount of data in health care is rapidly rising, leading to multiple datasets generated for any given individual. Data integration involves mapping variables in different datasets together to form a combined dataset which can then be ...