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数据挖掘以了解创伤性脑损伤之前的健康状况。

Data mining to understand health status preceding traumatic brain injury.

机构信息

Toronto Rehabilitation Institute-University Health Network, Toronto, Canada.

Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.

出版信息

Sci Rep. 2019 Apr 3;9(1):5574. doi: 10.1038/s41598-019-41916-5.

Abstract

The use of precision medicine is poised to increase in complex injuries such as traumatic brain injury (TBI), whose multifaceted comorbidities and personal circumstances create significant challenges in the domains of surveillance, management, and environmental mapping. Population-wide health administrative data remains a rather unexplored, but accessible data source for identifying clinical associations and environmental patterns that could lead to a better understanding of TBIs. However, the amount of data structured and coded by the International Classification of Disease poses a challenge to its successful interpretation. The emerging field of data mining can be instrumental in helping to meet the daunting challenges faced by the TBI community. The report outlines novel areas for data mining relevant to TBI, and offers insight into how the above approach can be applied to solve pressing healthcare problems. Future work should focus on confirmatory analyses, which subsequently can guide precision medicine and preventive frameworks.

摘要

精准医学的应用有望在复杂损伤中增加,例如创伤性脑损伤 (TBI),其多方面的合并症和个人情况在监测、管理和环境映射领域带来了重大挑战。人群健康管理数据仍然是一个相当未被探索的,但可访问的数据来源,可用于识别可能导致更好地理解 TBI 的临床关联和环境模式。然而,国际疾病分类所结构化和编码的数据量对其成功解释构成了挑战。新兴的数据挖掘领域可以帮助应对 TBI 社区面临的艰巨挑战。该报告概述了与 TBI 相关的数据挖掘新领域,并深入探讨了如何应用上述方法来解决紧迫的医疗保健问题。未来的工作应侧重于验证性分析,随后可以指导精准医学和预防框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60e3/6447542/9ecdb149fc8b/41598_2019_41916_Fig1_HTML.jpg

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