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

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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Publication Details

Journal
Journal of Cardiovascular Intervention
Published
2025-01-01
DOI
https://doi.org/10.54912/jci.2025.0020
Citations
1
Primary Topic
Clinical Reasoning and Diagnostic Skills
Type
article
Field-Weighted Citation Impact
1.52
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article

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

In‐Ho Chae, Tae Jin Yun, Ki‐Hyun Jeon
1 citations
Journal of Cardiovascular Intervention
Clinical Reasoning and Diagnostic Skills
1.52
article

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

In‐Ho Chae, Tae Jin Yun, Ki‐Hyun Jeon
article en
1 citations

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.

Journal of Cardiovascular InterventionVol. 4(4)
Seoul National University Bundang Hospital (KR)
Openalex Percentile: Top 15%
Clinical Reasoning and Diagnostic Skills
1.52
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