ChatGPT and Medical Statistics: A Narrative Review on Opportunities, Pitfalls, and the Principle of “Trust, but Verify”

Abstract

Statistical analysis is essential for drawing meaningful conclusions and ensuring the validity and reliability of medical research.However, many researchers face challenges due to the complexity of statistical techniques.Recent advances in artificial intelligence, particularly large language models such as ChatGPT, offer new opportunities to make statistical processes more accessible.ChatGPT can explain complex statistical concepts in plain language, assist with data management, generate Python code for various analyses, and create visualizations using natural language instructions.These capabilities enable researchers without advanced coding or statistical training to conduct meaningful analyses.Nevertheless, ChatGPT's outputs must be interpreted with caution.While ChatGPT primarily generates code rather than direct conclusions, thereby reducing the risk of hallucination, users must still carefully verify whether the generated code is appropriate and efficient.ChatGPT does not possess a true understanding of statistical concepts and may overlook important details in analysis.Data privacy is an additional concern.Researchers must avoid sharing sensitive information and comply with data protection regulations.When used responsibly, ChatGPT can serve as a powerful assistant, improving the efficiency, quality, and accessibility of statistical analysis in cardiovascular research.Importantly, human experts must continue to review and guide the research process to ensure scientific accuracy and uphold ethical standards.

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