基于人工智能的药丸计数应用中的陷阱评估。
Assessment of Pitfalls in an AI-Based Pill-Counting Application.
作者信息
Tanamachi Namie, Amemiya Takahiro, Tomita Takashi
机构信息
Department of Pharmacy, International University of Health and Welfare Mita Hospital, Minato, JPN.
Department of Pharmaceutical Sciences, Teikyo Heisei University, Nakano, JPN.
出版信息
Cureus. 2025 Aug 23;17(8):e90837. doi: 10.7759/cureus.90837. eCollection 2025 Aug.
Artificial intelligence (AI)-based pill-counting applications have been introduced into clinical practice to streamline the work of pharmacists. However, no study has evaluated the safety of these drugs. The purpose of this study was to evaluate AI's ability to recognize Yakushimarukazuko (NeoX Inc., Tokyo, Japan) and identify operational issues. The results confirmed that the transparency, overlap, and direction of the supplements used in the assessment were important factors in AI-based recognition. Accurately identifying and addressing such operational issues with AI-based pill-counting applications will contribute to minimizing the risk of errors and, in turn, enhance medical safety.
基于人工智能（AI）的药丸计数应用已被引入临床实践，以简化药剂师的工作。然而，尚无研究评估这些药物的安全性。本研究的目的是评估人工智能识别Yakushimarukazuko（日本东京NeoX公司）的能力，并识别操作问题。结果证实，评估中使用的补充剂的透明度、重叠度和方向是基于人工智能识别的重要因素。通过基于人工智能的药丸计数应用准确识别和解决此类操作问题，将有助于最大限度地降低错误风险，进而提高医疗安全性。
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