基于数据挖掘的CRC肠道菌群营养干预可行性分析

Feasibility analysis of CRC intestinal flora nutrition intervention based on data Mining

随着智能技术与医疗健康领域融合的加深,正在不断提升着医疗服务水平。科学研究已经证明:结直肠癌的发生与肠道菌群存在密切关系。将人工智能运用在结直肠癌(CRC)肠道菌群营养干预上,可以帮助优化资源分配,提高医疗各环节的效率,提升诊疗效果。本文以五种常见肠道菌群为基础,结合数据挖掘的K-Means和Apriori算法,分析了基于数据挖掘的CRC肠道菌群营养干预的可行性。

With the deepening of the integration of intelligent technology and medical and health care,the level of medical services is constantly improving. Scientific research has proved that the occurrence of colorectal cancer is closely related to intestinal flora. The application of artificial intelligence in the nutritional intervention of colorectal cancer(CRC) intestinal flora can help optimize the allocation of resources,improve the efficiency of all aspects of medical treatment and improve the effect of diagnosis and treatment. Based on five common intestinal flora and combined with k-means and Apriori algorithms of data mining,this paper analyzed the feasibility of nutrition intervention for CRC intestinal flora based on data mining.