■ChatGPT,最先进的大型语言模型,在分析图像和提供准确信息方面显示出潜力。这项研究旨在探索ChatGPT-4作为识别不同版本和测试日期的常用处方肾病药物的工具。
■从一家机构药房获得25种肾病药物。使用iPhone13ProMax捕获每种药物的高质量图像,并与查询一起上传到ChatGPT-4,\'这是什么药物?\'ChatGPT-4的反应的准确性被评估为药物名称,剂量,和印记。2周后重复该过程,以评估不同版本之间的一致性,包括GPT-4,GPT-4传统,GPT-4Ø
■ChatGPT-4在所有版本中正确识别了25种(88%)药物中的22种。然而,它误认了氢氯噻嗪,硝苯地平,和螺内酯由于误读印记。例如,硝苯地平ER90mg被误认为是盐酸二甲双胍ER500mg,因为“NF06”被误认为是“NF05”。由于印记错误,氢氯噻嗪50毫克与25毫克版本混淆,和螺内酯25mg被误认为是萘普生钠或双氯芬酸钠。尽管有这些错误,ChatGPT-4在重新测试时显示出100%的一致性,在收到关于正确印记的反馈后纠正错误识别。
ChatGPT-4在从自我捕获的图像中识别肾病药物方面显示出强大的潜力,尽管难以阅读的印记仍然存在挑战。提供反馈,提高准确性,这表明ChatGPT-4可能是数字健康中用于药物识别的有价值的工具。未来的研究应该增强模型区分类似印记的能力,并探索更广泛地整合到数字健康平台中。
UNASSIGNED: ChatGPT, a state-of-the-art large language model, has shown potential in analyzing images and providing accurate information. This study aimed to explore ChatGPT-4 as a tool for identifying commonly prescribed
nephrology medications across different versions and testing dates.
UNASSIGNED: 25
nephrology medications were obtained from an institutional pharmacy. High-quality images of each medication were captured using an iPhone 13 Pro Max and uploaded to ChatGPT-4 with the query, \'What is this medication?\' The accuracy of ChatGPT-4\'s responses was assessed for medication name, dosage, and imprint. The process was repeated after 2 weeks to evaluate consistency across different versions, including GPT-4, GPT-4 Legacy, and GPT-4.Ø.
UNASSIGNED: ChatGPT-4 correctly identified 22 out of 25 (88%) medications across all versions. However, it misidentified Hydrochlorothiazide, Nifedipine, and Spironolactone due to misreading imprints. For instance, Nifedipine ER 90 mg was mistaken for Metformin Hydrochloride ER 500 mg because \'NF 06\' was misread as \'NF 05\'. Hydrochlorothiazide 50 mg was confused with the 25 mg version due to imprint errors, and Spironolactone 25 mg was misidentified as Naproxen Sodium or Diclofenac Sodium. Despite these errors, ChatGPT-4 showed 100% consistency when retested, correcting misidentifications after receiving feedback on the correct imprints.
UNASSIGNED: ChatGPT-4 shows strong potential in identifying
nephrology medications from self-captured images, though challenges with difficult-to-read imprints remain. Providing feedback improved accuracy, suggesting ChatGPT-4 could be a valuable tool in digital health for medication identification. Future research should enhance the model\'s ability to distinguish similar imprints and explore broader integration into digital health platforms.