Multi-omics graph convolutional networks for digestive system tumour classification and early-late stage diagnosis  

作　　者：Lin Zhou Zhengzhi Zhu Hongbo Gao Chunyu Wang Muhammad Attique Khan Mati Ullah Siffat Ullah Khan 

机构地区：[1]School of Information Science and Technology,University of Science and Technology of China,Hefei,Anhui,China [2]Anhui Engineering Research Center on Information Fusion and Control of Intelligent Robot,Wuhu,Anhui,China [3]Department of Breast Center,West District of The Affiliated Hospital of University of Science and Technology of China,Division of Life Sciences and Medicine,University of Science and Technology of China,Hefei,Anhui,China [4]Institute of Advanced Technology,University of Science and Technology of China,Hefei,Anhui,China [5]School of Electrical and Electronic Engineering,Nanyang Technological University,Singapore,Singapore [6]School of Biological and Environmental Engineering,Chaohu University,Chaohu Regional Collaborative Technology Service Center for Rural Revitalization,Hefei,China [7]Department of Artificial Intelligence,College of Computer Engineering and Science,Prince Mohammad Bin Fahd University,Al-Khobar,Saudi Arabia [8]School of Automation,Northwestern Polytechnical University,Xi'an,Shaanxi,China [9]Institute of Engineering and Computing Science,University of Science and Technology of Bannu,KPK,Bannu,Pakistan

出　　处：《CAAI Transactions on Intelligence Technology》2024年第6期1572-1586,共15页智能技术学报(英文)

基　　金：Science and Technology Innovation 2030-“New Generation Artificial Intelligence”Major Project,Grant/Award Number:2022ZD0116305;Anhui Province Natural Science Funds for Distinguished Young Scholar,Grant/Award Number:2308085J02;National Natural Science Foundation of China,Grant/Award Numbers:U2013601,U20A20225,42107112,32070670;Innovation Leading Talent of Anhui Province TeZhi plan;CAAI-Huawei Mind Spore Open Fund,Grant/Award Number:CAAIXSJLJJ-2022-011A;Natural Science Foundation of Hefei,China,Grant/Award Number:202321。

摘　　要：The prevalence of digestive system tumours(DST)poses a significant challenge in the global crusade against cancer.These neoplasms constitute 20%of all documented cancer diagnoses and contribute to 22.5%of cancer-related fatalities.The accurate diagnosis of DST is paramount for vigilant patient monitoring and the judicious selection of optimal treatments.Addressing this challenge,the authors introduce a novel methodology,denominated as the Multi-omics Graph Transformer Convolutional Network(MGTCN).This innovative approach aims to discern various DST tumour types and proficiently discern between early-late stage tumours,ensuring a high degree of accuracy.The MGTCN model incorporates the Graph Transformer Layer framework to meticulously transform the multi-omics adjacency matrix,thereby illuminating potential associations among diverse samples.A rigorous experimental evaluation was undertaken on the DST dataset from The Cancer Genome Atlas to scrutinise the efficacy of the MGTCN model.The outcomes unequivocally underscore the efficiency and precision of MGTCN in diagnosing diverse DST tumour types and successfully discriminating between early-late stage DST cases.The source code for this groundbreaking study is readily accessible for download at https://github.com/bigone1/MGTCN.

关 键 词：digestive system tumors early-late stage multi-omics tumor types 

分 类 号：R73[医药卫生—肿瘤]