This paper is in the following e-collection/theme issue:

Foundations of AI (47) Artificial Intelligence (1421) AI Data (13) Research Methodology - AI (14)

Published on in Vol 2 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45000, first published .
Artificial Intelligence–Enabled Software Prototype to Inform Opioid Pharmacovigilance From Electronic Health Records: Development and Usability Study

Artificial Intelligence–Enabled Software Prototype to Inform Opioid Pharmacovigilance From Electronic Health Records: Development and Usability Study

Artificial Intelligence–Enabled Software Prototype to Inform Opioid Pharmacovigilance From Electronic Health Records: Development and Usability Study

Authors of this article:

Alfred Sorbello1 Author Orcid Image ;   Syed Arefinul Haque1 Author Orcid Image ;   Rashedul Hasan1 Author Orcid Image ;   Richard Jermyn2 Author Orcid Image ;   Ahmad Hussein2 Author Orcid Image ;   Alex Vega2 Author Orcid Image ;   Krzysztof Zembrzuski2 Author Orcid Image ;   Anna Ripple3 Author Orcid Image ;   Mitra Ahadpour1 Author Orcid Image
Article Authors Cited by (2) Tweetations (3) Metrics

Journals

  1. Bhattarai K, Oh I, Sierra J, Tang J, Payne P, Abrams Z, Lai A. Leveraging GPT-4 for identifying cancer phenotypes in electronic health records: a performance comparison between GPT-4, GPT-3.5-turbo, Flan-T5, Llama-3-8B, and spaCy’s rule-based and machine learning-based methods. JAMIA Open 2024;7(3) View
  2. Zhang X, Tsang C, Ford D, Wang J. Student Pharmacists’ Perceptions of Artificial Intelligence and Machine Learning in Pharmacy Practice and Pharmacy Education. American Journal of Pharmaceutical Education 2024:101309 View