Kenichi Yamamura
Transgenic Group, Inc., Fukuoka, Japan
Publications
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Research Article
Limitations of Generative AI for Numerical Aggregation of Apple Health Step Count Data: A Validation Study Using XML Records, Manual Calculation, and Health Auto Export
Author(s): Zhenghua Li and Kenichi Yamamura*
Background: Generative artificial intelligence (AI) tools are increasingly used to assist data handling and research workflows. However, their reliability for numerical aggregation of raw health data has not been fully validated. Objective: This study examined whether generative AI could accurately aggregate Apple Health step count data from original XML records and compared the results with manual calculation and Health Auto Export. Methods: Step count records were extracted from Apple Health XML data. The original data consisted of multiple measurement records per day. Daily step counts were calculated using four approaches: two independent aggregations using Apple Intelligence plus ChatGPT, Health Auto Export, and manual calculation in Excel from the original XML- derived records. Daily totals and weekly summaries were compared across met.. Read More»