青岛大学学报（自然科学版）2024，Vol.37Issue(1)：27-31,38,6.DOI:10.3969/j.issn.1006-1037.2024.01.05
基于微生物转移网络的疾病检测算法
Disease Detection Algorithms Based on Microbial Transfer Network
摘要
Abstract
A novel graph neural network algorithm(SAGE-O-N)based on microbial transfer network was proposed for disease detection,which addressed the problem of ignoring potential microbial associations in disease detection methods.The similarity features of microbial sequencing information was utilized to con-struct a microbial transfer network,and a graph-structured data mining algorithm was used to uncover similarity and phenotypic associations.Experimental results show that SAGE-O-N improves the area un-der curve(AUC)of subjects'working characteristics on a single disease by about 2%,and the AUC in the comorbidity dataset by about 4%,compared with traditional machine learning methods.关键词
图神经网络/疾病检测/人体菌群/微生物转移网络Key words
graph neural network/disease detection/microbiota sequencing/microbial transfer network分类
信息技术与安全科学引用本文复制引用
孙洪杰,吴舜尧..基于微生物转移网络的疾病检测算法[J].青岛大学学报（自然科学版）,2024,37(1):27-31,38,6.基金项目
山东省自然科学基金(批准号:ZR2019PF012)资助 （批准号:ZR2019PF012）
山东省高等学校科技计划(批准号:J18KA356)资助. （批准号:J18KA356）
