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arXiv 1503.06316cs.CEcs.AI
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使用自组织地图识别相似患者:1型糖尿病自我护理调查响应的案例研究

Identifying Similar Patients Using Self-Organising Maps: A Case Study on Type-1 Diabetes Self-care Survey Responses

University of Surrey(萨里大学)

Santosh Tirunagari, Norman Poh, Guosheng Hu, David Windridge

摘要:

糖尿病被认为是一种生活方式疾病,良好的自我护理在治疗中起着重要作用。临床医生经常进行调查,以了解他们的病人的自我护理行为。在这种情况下,我们建议使用自组织地图(SOM),以探讨调查数据评估的自我护理行为的1型糖尿病患者。具体来说,SOM是用来可视化高维相似的病人档案,这是很少讨论。实验表明,我们的研究结果,通过SOM分析符合临床医生的期望。此外,我们的研究结果启发了专家,以提高他们的理解,为他们的病人的自我护理行为。我们研究的主要发现表明:1)服用正确剂量胰岛素的患者,在正确的时间注射胰岛素,2)服用正确食物部分的患者进行定期体力活动,3)按时进食的患者服用正确的食物部分。

英文摘要:

Diabetes is considered a lifestyle disease and a well managed self-care plays an important role in the treatment. Clinicians often conduct surveys to understand the self-care behaviors in their patients. In this context, we propose to use Self-Organising Maps (SOM) to explore the survey data for assessing the self-care behaviors in Type-1 diabetic patients. Specifically, SOM is used to visualize high dimensional similar patient profiles, which is rarely discussed. Experiments demonstrate that our findings through SOM analysis corresponds well to the expectations of the clinicians. In addition, our findings inspire the experts to improve their understanding of the self-care behaviors for their patients. The principle findings in our study show: 1) patients who take correct dose of insulin, inject insulin at the right time, 2) patients who take correct food portions undertake regular physical activity and 3) patients who eat on time take correct food portions.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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