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Comprehensive reporting guidelines and checklist for studies developing and utilizing artificial intelligence models.

Sang Gyu Kwak1, Jonghae Kim2

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PubMed
Summary

New guidelines and a checklist standardize reporting for artificial intelligence (AI) in healthcare research. This ensures transparency, reproducibility, and ethical AI applications, regardless of study design.

Keywords:
Artificial intelligenceHealth care researchMachine learningReproducibility of resultsStatistical modelsStatistics

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Area of Science:

  • Medical Informatics
  • Artificial Intelligence in Medicine
  • Clinical Research Methodology

Background:

  • Rapid advancements in artificial intelligence (AI) in healthcare require standardized reporting.
  • Current standards are limited by study design specificity.
  • Need for comprehensive guidelines for AI development and utilization in clinical research.

Purpose of the Study:

  • Develop comprehensive guidelines and a checklist for reporting AI model studies in healthcare.
  • Cover all essential components of AI research irrespective of study design.
  • Enhance transparency, reproducibility, and ethical AI applications.

Main Methods:

  • Guidelines and checklist developed by biostatistics experts.
  • Key AI model reporting elements identified and structured.
  • Iterative review and feedback from clinicians and researchers incorporated.

Main Results:

  • A detailed checklist for AI model reporting was created.
  • Guidelines cover study design, data, model training, evaluation, ethics, and implementation.
  • Comprehensive details on AI specifications and data handling are provided.

Conclusions:

  • The guidelines and checklist serve as valuable tools for AI in healthcare research.
  • Promote reliability, accountability, and ethical AI use.
  • Address critical aspects of AI reporting for improved research integrity.