Meo Anusha S, Shaikh Narmeen, Meo Sultan A
From the The School of Medicine (AS Meo), Medical Sciences and Nutrition, University of Aberdeen, Scotland, United Kingdom; from the College of Medicine (Shaikh), King Saud University; and from the Department of Physiology (SA Meo), College of Medicine, King Saud University, Riyadh, Kingdom of Saudi Arabia.
Saudi Med J. 2024 Dec;45(12):1383-1390. doi: 10.15537/smj.2024.45.12.20240454.
To assess the accuracy of ChatGPT-4 Omni (GPT-4o) in biomedical statistics. The recent novel inauguration of Artificial Intelligence ChatGPT-Omni (GPT-4o), has emerged with the potential to analyze sophisticated and extensive data sets, challenging the expertise of statisticians using traditional statistical tools for data analysis.
This study was performed in the Department of Physiology, College of Medicine, King Saud University, Riyadh, Saudi Arabia, in May 2024. Three datasets in a raw Excel file format were imported onto Statistical Package for the Social Sciences (SPSS) version 29 for data analysis. Based on this analysis, a script of 9 questions was prepared to command GPT-4 Omni, which was used for data analysis for all 3 datasets on Omni. The score and the time were recorded for each result and verified after being compared to the original analysis results performed on SPSS.
GPT-4 Omni scored 73 (85.88%) out of 85 points for all 3 datasets. All datasets took a total of 38.43 minutes to be fully analyzed. Individually, Omni scored 21/25 (84%) for the small dataset in 487.4 seconds, 20/25 (80%) for the middle dataset in 747.02 seconds and 32/35 (91.42%) for the large dataset in 1071 seconds. GPT-4 Omni produced accurate graphs and charts.
ChatGPT-4 Omni scored better over 80% in all 3 statistical datasets in a short period. GPT-4 Omni also produced accurate graphs and charts as commanded however it required explicit commands with clear instructions to avoid errors and omission of results to achieve appropriate results in biomedical data analysis.
评估ChatGPT-4 Omni(GPT-4o)在生物医学统计学方面的准确性。最近新推出的人工智能ChatGPT-Omni(GPT-4o),具有分析复杂且广泛数据集的潜力,这对使用传统统计工具进行数据分析的统计学家的专业能力构成了挑战。
本研究于2024年5月在沙特阿拉伯利雅得国王沙特大学医学院生理学系进行。将三个原始Excel文件格式的数据集导入社会科学统计软件包(SPSS)版本29进行数据分析。基于此分析,准备了一个包含9个问题的脚本以指令GPT-4 Omni,该脚本用于对Omni上的所有3个数据集进行数据分析。记录每个结果的得分和时间,并与在SPSS上进行的原始分析结果进行比较后进行验证。
对于所有3个数据集,GPT-4 Omni在85分中得分为73分(85.88%)。所有数据集完全分析共耗时38.43分钟。单独来看,Omni对小数据集在487.4秒内得21/25(84%)分,对中数据集在747.02秒内得20/25(80%)分,对大数据集在1071秒内得32/35(91.42%)分。GPT-4 Omni生成了准确的图表。
ChatGPT-4 Omni在短时间内对所有3个统计数据集的得分均超过80%。GPT-4 Omni也能按指令生成准确的图表,然而在生物医学数据分析中,它需要带有清晰说明的明确指令,以避免错误和结果遗漏,从而获得恰当的结果。