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

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收录情况: ◇ SCIE ◇ 统计源期刊 ◇ CSCD-C

机构: [1]Tsinghua Univ, Dept Chem Engn, Beijing 100084, Peoples R China [2]Tsinghua Univ, Key Lab Ind Biocatalysis, Minist Educ, Beijing 100084, Peoples R China [3]Capital Med Univ, Xuanwu Hosp, Dept Cardiol, Beijing 100053, Peoples R China [4]Tsinghua Univ, Beijing Tsinghua Changgung Hosp, Sch Clin Med, Dept Cardiol, Beijing 102218, Peoples R China [5]Tsinghua Univ, Inst Biopharmaceut & Hlth Engn, Shenzhen Int Grad Sch, Shenzhen 518055, Peoples R China
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关键词: Black phosphorus/MXene heterostructures Light-activated virtual sensor array Diagnosis of coronary heart disease Machine learning

摘要:
Photoresponsive black phosphorus (BP)/Ti3C2Tx composites were synthesized by a self-assembly strategy.Enhanced gas sensitive property was achieved by visible light modulation.Light activated virtual sensor array was fabricated based on BP/Ti3C2Tx composite.Diagnosis of coronary heart disease was achieved with the help of machine learning. 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/Ti3C2Tx 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 Ti3C2Tx as well as photo excitation, the synthesized heterostructured complexes exhibited higher performance than pristine Ti3C2Tx, with a response value 26% higher than that of pristine Ti3C2Tx. 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.

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出版当年[2023]版:
大类 | 1 区 材料科学
小类 | 1 区 材料科学:综合 1 区 纳米科技 1 区 物理:应用
最新[2025]版:
大类 | 1 区 材料科学
小类 | 1 区 材料科学:综合 1 区 纳米科技 1 区 物理:应用
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出版当年[2022]版:
Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY Q1 NANOSCIENCE & NANOTECHNOLOGY Q1 PHYSICS, APPLIED
最新[2023]版:
Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY Q1 NANOSCIENCE & NANOTECHNOLOGY Q1 PHYSICS, APPLIED

影响因子: 最新[2023版] 最新五年平均 出版当年[2022版] 出版当年五年平均 出版前一年[2021版] 出版后一年[2023版]

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第一作者机构: [1]Tsinghua Univ, Dept Chem Engn, Beijing 100084, Peoples R China [2]Tsinghua Univ, Key Lab Ind Biocatalysis, Minist Educ, Beijing 100084, Peoples R China
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通讯机构: [1]Tsinghua Univ, Dept Chem Engn, Beijing 100084, Peoples R China [2]Tsinghua Univ, Key Lab Ind Biocatalysis, Minist Educ, Beijing 100084, Peoples R China
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