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Editorial
. 2025 Jan 10;18(Suppl 1):8.
doi: 10.1186/s12920-024-02072-6.

Challenges of reproducible AI in biomedical data science

Henry Han  1
Affiliations
Editorial

Challenges of reproducible AI in biomedical data science

Henry Han. BMC Med Genomics. .

Abstract

Artificial intelligence (AI) is revolutionizing biomedical data science at an unprecedented pace, transforming various aspects of the field with remarkable speed and depth. However, a critical issue remains unclear: how reproducible are the AI models and systems employed in biomedical data science? In this study, we examine the challenges of AI reproducibility by analyzing the factors influenced by data, model, and learning complexities, as well as through a game-theoretical perspective. While adherence to reproducibility standards is essential for the long-term advancement of AI, the conflict between following these standards and aligning with researchers' personal goals remains a significant hurdle in achieving AI reproducibility.

Keywords: AI; Biomedical data; Game-theory; Reproducibility.

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Conflict of interest statement

Declarations. Competing interests: Not applicable.

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