基于SEER乳腺癌数据的关联规则挖掘预测乳腺癌复发

2015 International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT) Pub Date : 2015-12-01 DOI:10.1109/ERECT.2015.7499044

D. Umesh, B. Ramachandra

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引用次数: 18

摘要

在包括印度在内的发达国家，乳腺癌是女性最常见的癌症。乳腺癌可能随时在乳腺癌幸存者中复发，但基本上在治疗后的最初三到五年内复发。在本文中，我们研究了在SEER(监测、流行病学和最终结果)数据集上利用关联规则挖掘临床肿瘤医生乳腺癌复发预期的可行性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Association rule mining based predicting breast cancer recurrence on SEER breast cancer data

Breast cancer is the most well-known type of cancer in women in the developed nations including India. Breast cancer could recur anytime in the breast cancer survivors, however basically it returns in the initial three to five years after the treatment. In this paper we investigate the feasibility of utilizing an association rule mining for a clinical oncology doctor in expectation of breast cancer recurrence on SEER (Surveillance, Epidemiology, and End Results) dataset.

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来源期刊

2015 International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)

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