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Guidelines for reporting artificial intelligence studies in medicines, pharmacotherapy, and pharmaceutical services:
Wallace Entringer Bottacin1, Thais Teles de Souza2, Walleri Christini Torelli Reis3
1Postgraduate Program in Pharmaceutical Services and Policies, Federal University of Paraná, Avenida Prefeito Lothário Meissner, 632 - Jardim Botânico, Curitiba, PR, CEP 80210-170, Brazil. wallace.bottacin@gmail.com.
New MedinAI guidelines enhance transparency in artificial intelligence (AI) research for medicines and pharmaceutical services. These validated guidelines promote reproducible and ethical AI development in healthcare.
Area of Science:
- Pharmaceutical Sciences
- Medical Informatics
- Artificial Intelligence in Healthcare
Background:
- Expanding applications of artificial intelligence (AI) in medicines, pharmacotherapy, and pharmaceutical services.
- Lack of standardized reporting guidelines hinders transparency, comparability, and reproducibility in AI-driven healthcare research.
Purpose of the Study:
- To develop and validate comprehensive reporting guidelines for AI studies in medicines, pharmacotherapy, and pharmaceutical services.
- Establish standardized reporting to improve evidence-based healthcare decision-making.
Main Methods:
- Utilized a two-phase approach based on the Moher Guidance for Developers of Health Research Reporting Guidelines.
- Phase 1: Literature reviews and expert discussions for initial drafting.
- Phase 2: Delphi method with 26 international experts for validation and refinement, achieving consensus on items.
Main Results:
- Developed the MedinAI guidelines, comprising 14 items and 78 sub-items across four domains.
- Achieved high consensus (median=8, 95.2% agreement) for all items, indicating publication readiness.
- MedinAI guidelines are adaptable to various AI development stages and align with existing EQUATOR Network reporting standards.
Conclusions:
- MedinAI provides validated reporting guidelines for AI in medicines, pharmacotherapy, and pharmaceutical services.
- Promotes transparency, comparability, and reproducibility in AI research within these fields.
- Facilitates responsible and ethical AI development and application in healthcare.
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