Five critical quality criteria for artificial intelligence-based prediction models

Key Result

The European Heart Journal editors propose five minimal quality criteria for AI-based prediction models: complete reporting, clear intended use, rigorous validation, adequate sample size, and open code.

Key Points

• The aim is to establish minimal quality criteria for developing and validating AI prediction models in cardiovascular health.
• Proposed five criteria: complete reporting, defined intended use, rigorous validation, adequate sample size, and openness of code.
• Focus on improving the impact and relevance of AI in clinical settings.
• Emphasis on complete reporting to ensure transparency.
• Rigorous validation is crucial for credibility and effectiveness of models.
• Large sample sizes are necessary to enhance the reliability of the predictions.