ArticleJournal of medical Internet research2025
ChatGPT for Univariate Statistics: Validation of AI-Assisted Data Analysis in Healthcare Research.
Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Article
- Can large language models accurately compute descriptive statistics from structured datasets? A comparative evaluation of ChatGPT and Claude.American heart journal plus : cardiology research and practice · 2026Article
- Article
- Evaluating the performance of ChatGPT-5, Claude, and DeepSeek for statistical analysis in medicine.Internal and emergency medicine · 2026Article
- Applications of Large Language Models in Medical Research: From Systematic Reviews to Clinical Studies.Bioengineering (Basel, Switzerland) · 2026Review
- A structured framework for effective and responsible generative artificial intelligence chatbot prompt engineering throughout the scientific process: a comprehensive guide for the health and medical researcher.Frontiers in artificial intelligence · 2026Review
- Prompt engineering for generative artificial intelligence chatbots in health research: A practical guide for traditional, complementary, and integrative medicine researchers.Integrative medicine research · 2025Article
- Statistical analysis using ChatGPT in medical research.Obstetrics & gynecology science · 2025Article
- Artificial Intelligence in Action: Racial and Gender Disparities in Academic Radiology.Cureus · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundChatGPT, a conversational artificial intelligence developed by OpenAI, has rapidly become an invaluable tool for researchers. With the recent integration of Python code interpretation into the ChatGPT environment, there has been a significant increase in the potential utility of ChatGPT as a research tool, particularly in terms of data analysis applications.
objectiveThis study aimed to assess ChatGPT as a data analysis tool and provide researchers with a framework for applying ChatGPT to data management tasks, descriptive statistics, and inferential statistics.
methodsA subset of the National Inpatient Sample was extracted. Data analysis trials were divided into data processing, categorization, and tabulation, as well as descriptive and inferential statistics. For data processing, categorization, and tabulation assessments, ChatGPT was prompted to reclassify variables, subset variables, and present data, respectively. Descriptive statistics assessments included mean, SD, median, and IQR calculations. Inferential statistics assessments were conducted at varying levels of prompt specificity ("Basic," "Intermediate," and "Advanced"). Specific tests included chi-square, Pearson correlation, independent 2-sample t test, 1-way ANOVA, Fisher exact, Spearman correlation, Mann-Whitney U test, and Kruskal-Wallis H test. Outcomes from consecutive prompt-based trials were assessed against expected statistical values calculated in Python (Python Software Foundation), SAS (SAS Institute), and RStudio (Posit PBC).
resultsChatGPT accurately performed data processing, categorization, and tabulation across all trials. For descriptive statistics, it provided accurate means, SDs, medians, and IQRs across all trials. Inferential statistics accuracy against expected statistical values varied with prompt specificity: 32.5% accuracy for "Basic" prompts, 81.3% for "Intermediate" prompts, and 92.5% for "Advanced" prompts.
conclusionsChatGPT shows promise as a tool for exploratory data analysis, particularly for researchers with some statistical knowledge and limited programming expertise. However, its application requires careful prompt construction and human oversight to ensure accuracy. As a supplementary tool, ChatGPT can enhance data analysis efficiency and broaden research accessibility.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.