Suppr超能文献

一种用于分析乳腺癌治疗指南不依从情况的数据挖掘方法。

A data mining approach to analyze non-compliance with a guideline for the treatment of breast cancer.

作者信息

Razavi Amir R, Gill Hans, Ahlfeldt Hans, Shahsavar Nosrat

机构信息

Department of Biomedical Engineering, Division of Medical Informatics, Linköping University, Sweden.

出版信息

Stud Health Technol Inform. 2007;129(Pt 1):591-5.

Abstract

Postmastectomy radiotherapy (PMRT) is prescribed in order to reduce the local recurrence of breast cancer and improve overall survival. A guideline supports the trade-off between benefits and adverse effects of PMRT. However, this guideline is not always followed in practice. This study tries to find a method for revealing patterns of non-compliance between the actual treatment and the PMRT guideline. Data from breast cancer patients admitted to Linköping University Hospital between 1990 and 2000 were analyzed in this study. Cases that were not treated in accordance with the guideline were selected and analyzed by decision tree induction (DTI). Thereafter, four resulting rules, as representations for groups of patients, were compared to the guideline. Finding patterns of non-compliance with guidelines by means of rules can be an appropriate alternative to manual methods, i.e. a case-by-case comparison when studying very large datasets. The resulting rules can be used in a knowledge base of a guideline-based decision support system to alert when inconsistencies with the guidelines may appear.

摘要

乳房切除术后放疗(PMRT)的目的是降低乳腺癌的局部复发率并提高总体生存率。一项指南支持在PMRT的益处和不良反应之间进行权衡。然而,在实际操作中,该指南并非总是得到遵循。本研究试图找到一种方法来揭示实际治疗与PMRT指南之间的不依从模式。本研究分析了1990年至2000年间入住林雪平大学医院的乳腺癌患者的数据。选择未按照指南进行治疗的病例,并通过决策树归纳法(DTI)进行分析。此后,将作为患者群体代表的四条最终规则与指南进行比较。通过规则来发现与指南不相符的模式可以作为手动方法的一种合适替代方案,即在研究非常大的数据集时进行逐案比较。最终规则可用于基于指南的决策支持系统的知识库中,以便在可能出现与指南不一致的情况时发出警报。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验