Light-Activated Virtual Sensor Array with Machine Learning for Non-Invasive Diagnosis of Coronary Heart Disease  

作　　者：Jiawang Hu Hao Qian Sanyang Han Ping Zhang Yuan Lu 

机构地区：[1]Department of Chemical Engineering,Tsinghua University,Beijing 100084,People’s Republic of China [2]Key Laboratory of Industrial Biocatalysis,Ministry of Education,Tsinghua University,Beijing 100084,People’s Republic of China [3]Department of Cardiology,Xuanwu Hospital,Capital Medical University,Beijing 100053,People’s Republic of China [4]Department of Cardiology,Beijing Tsinghua Changgung Hospital,School of Clinical Medicine,Tsinghua University,Beijing 102218,People’s Republic of China [5]Institute of Biopharmaceutical and Health Engineering,Shenzhen International Graduate School,Tsinghua University,Shenzhen 518055,People’s Republic of China

出　　处：《Nano-Micro Letters》2024年第12期427-448,共22页纳微快报（英文版）

基　　金：supported by the National Natural Science Foundation of China(22278241);the National Key R&D Program of China(2018YFA0901700);a grant from the Institute Guo Qiang,Tsinghua University(2021GQG1016);Department of Chemical Engineering-iBHE Joint Cooperation Fund.

摘　　要：Early non-invasive diagnosis of coronary heart disease(CHD)is critical.However,it is challenging to achieve accurate CHD diagnosis via detecting breath.In this work,heterostructured complexes of black phosphorus(BP)and two-dimensional carbide and nitride(MXene)with high gas sensitivity and photo responsiveness were formulated using a self-assembly strategy.A light-activated virtual sensor array(LAVSA)based on BP/Ti_(3)C_(2)Tx was prepared under photomodulation and further assembled into an instant gas sensing platform(IGSP).In addition,a machine learning(ML)algorithm was introduced to help the IGSP detect and recognize the signals of breath samples to diagnose CHD.Due to the synergistic effect of BP and Ti_(3)C_(2)Tx as well as photo excitation,the synthesized heterostructured complexes exhibited higher performance than pristine Ti_(3)C_(2)Tx,with a response value 26%higher than that of pristine Ti_(3)C_(2)Tx.In addition,with the help of a pattern recognition algorithm,LAVSA successfully detected and identified 15 odor molecules affiliated with alcohols,ketones,aldehydes,esters,and acids.Meanwhile,with the assistance of ML,the IGSP achieved 69.2%accuracy in detecting the breath odor of 45 volunteers from healthy people and CHD patients.In conclusion,an immediate,low-cost,and accurate prototype was designed and fabricated for the noninvasive diagnosis of CHD,which provided a generalized solution for diagnosing other diseases and other more complex application scenarios.

关 键 词：Black phosphorus/MXene heterostructures Light-activated virtual sensor array Diagnosis of coronary heart disease Machine learning 

分 类 号：TP212.9[自动化与计算机技术—检测技术与自动化装置] TP181[自动化与计算机技术—控制科学与工程] R541.4[医药卫生—心血管疾病]