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Automatic identification of prescription drugs using shape distribution models

机译:使用形状分布模型自动识别处方药

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Medication errors are one of the safety problems most frequently seen in hospital organizations. It is estimated that 12.2% of all hospitalized patients are involved in some form of adverse drug event (ADE) [1]. A significant amount of ADEs result from handing the incorrect drug to a patient or prescribing the wrong medication. This paper introduces a simple yet robust classification technique that can be used to automatically identify prescriptions drugs within images. The system uses a modified shape distribution technique to examine the shape, color, and imprint of a pill and create an invariant descriptor that can be used to recognize the same drug under different viewing conditions. The proposed technique has been successfully evaluated with 568 of the most prescribed drugs in the United States and has shown a 91.13% accuracy in automatically identifying the correct medication.
机译:用药错误是医院组织中最常见的安全问题之一。据估计,所有住院患者中有12.2%参与某种形式的药物不良事件(ADE)[1]。将不正确的药物交给患者或开出错误的药物会导致大量ADE。本文介绍了一种简单而强大的分类技术,该技术可用于自动识别图像中的处方药。该系统使用改进的形状分布技术来检查药丸的形状,颜色和印记,并创建一个不变的描述符,该描述符可用于在不同的观察条件下识别相同的药物。在美国,已使用568种最常用的药物成功评估了所提出的技术,在自动识别正确的药物方面显示出91.13%的准确性。

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