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利用相似患者的时间趋势预测患者生理数据轨迹:一种近期预后系统

Predicting Patient's Trajectory of Physiological Data using Temporal Trends in Similar Patients: A System for Near-Term Prognostics.

作者信息

Ebadollahi Shahram, Sun Jimeng, Gotz David, Hu Jianying, Sow Daby, Neti Chalapathy

机构信息

IBM T.J. Watson Research Center, Hawthorne, NY.

出版信息

AMIA Annu Symp Proc. 2010 Nov 13;2010:192-6.

Abstract

Providing near-term prognostic insight to clinicians helps them to better assess the near-term impact of their decisions and potential impending events affecting the patient. In this work, we present a novel system, which leverages inter-patient similarity for retrieving patients who display similar trends in their physiological time-series data. Data from the retrieved patient cohort is then used to project patient data into the future to provide insights for the query patient. The proposed approach and system were tested using the MIMIC II database, which consists of physiological waveforms, and accompanying clinical data obtained for ICU patients. In the experiments we report the effectiveness of the inter-patient similarity measure and the accuracy of the projection of patients' data. We also discuss the visual interface that conveys the near-term prognostic decision support to the user.

摘要

为临床医生提供近期预后洞察有助于他们更好地评估其决策的近期影响以及影响患者的潜在即将发生的事件。在这项工作中,我们提出了一种新颖的系统,该系统利用患者间的相似性来检索在其生理时间序列数据中显示出相似趋势的患者。然后,来自检索到的患者队列的数据被用于将患者数据投射到未来,以为查询患者提供洞察。所提出的方法和系统使用MIMIC II数据库进行了测试,该数据库由生理波形以及为ICU患者获得的伴随临床数据组成。在实验中,我们报告了患者间相似性度量的有效性以及患者数据投射的准确性。我们还讨论了向用户传达近期预后决策支持的可视化界面。

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