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Detecting manuscripts written by generative AI and AI-assisted technologies in the field of pharmacy practice.

Ammar Abdulrahman JairounFaris El-DahiyatGhaleb A ElRefaeSabaa Saleh Al-HemyariMoyad ShahwanSamer H ZyoudKhawla Abu HammourZaheer Ud-Din Babaar
Published in: Journal of pharmaceutical policy and practice (2024)
Generative AI can be a powerful research tool, but researchers must employ it ethically and transparently. This commentary addresses how the editors of pharmacy practice journals can identify manuscripts generated by generative AI and AI-assisted technologies. Editors and reviewers must stay well-informed about developments in AI technologies to effectively recognise AI-written papers. Editors should safeguard the reliability of journal publishing and sustain industry standards for pharmacy practice by implementing the crucial strategies outlined in this editorial. Although obstacles, including ignorance, time constraints, and protean AI strategies, might hinder detection efforts, several facilitators can help overcome those obstacles. Pharmacy practice journal editors and reviewers would benefit from educational programmes, collaborations with AI experts, and sophisticated plagiarism-detection techniques geared toward accurately identifying AI-generated text. Academics and practitioners can further uphold the integrity of published research through transparent reporting and ethical standards. Pharmacy practice journal staffs can sustain academic rigour and guarantee the validity of scholarly work by recognising and addressing the relevant barriers and utilising the proper enablers. Navigating the changing world of AI-generated content and preserving standards of excellence in pharmaceutical research and practice requires a proactive strategy of constant learning and community participation.
Keyphrases
  • artificial intelligence
  • primary care
  • healthcare
  • quality improvement
  • machine learning
  • deep learning
  • physical activity
  • mental health
  • decision making
  • quantum dots
  • electronic health record