利用机器学习的光激活虚拟传感器阵列用于冠心病的非侵入性诊断。

IF 26.6 1区材料科学 Q1 Engineering

Nano-Micro Letters Pub Date : 2024-08-16 DOI:10.1007/s40820-024-01481-7

Jiawang Hu, Hao Qian, Sanyang Han, Ping Zhang, Yuan Lu

{"title":"利用机器学习的光激活虚拟传感器阵列用于冠心病的非侵入性诊断。","authors":"Jiawang Hu, Hao Qian, Sanyang Han, Ping Zhang, Yuan Lu","doi":"10.1007/s40820-024-01481-7","DOIUrl":null,"url":null,"abstract":"<div><h2>Highlights</h2><div>\n \n <ul>\n <li>\n <p>Photoresponsive black phosphorus (BP)/Ti<sub>3</sub>C<sub>2</sub>T<sub>x</sub> composites were synthesized by a self-assembly strategy.</p>\n </li>\n <li>\n <p>Enhanced gas sensitive property was achieved by visible light modulation.</p>\n </li>\n <li>\n <p>Light activated virtual sensor array was fabricated based on BP/Ti<sub>3</sub>C<sub>2</sub>T<sub>x</sub> composite.</p>\n </li>\n <li>\n <p>Diagnosis of coronary heart disease was achieved with the help of machine learning.</p>\n </li>\n </ul>\n </div></div>","PeriodicalId":714,"journal":{"name":"Nano-Micro Letters","volume":"16 1","pages":""},"PeriodicalIF":26.6000,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11327237/pdf/","citationCount":"0","resultStr":"{\"title\":\"Light-Activated Virtual Sensor Array with Machine Learning for Non-Invasive Diagnosis of Coronary Heart Disease\",\"authors\":\"Jiawang Hu, Hao Qian, Sanyang Han, Ping Zhang, Yuan Lu\",\"doi\":\"10.1007/s40820-024-01481-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h2>Highlights</h2><div>\\n \\n <ul>\\n <li>\\n <p>Photoresponsive black phosphorus (BP)/Ti<sub>3</sub>C<sub>2</sub>T<sub>x</sub> composites were synthesized by a self-assembly strategy.</p>\\n </li>\\n <li>\\n <p>Enhanced gas sensitive property was achieved by visible light modulation.</p>\\n </li>\\n <li>\\n <p>Light activated virtual sensor array was fabricated based on BP/Ti<sub>3</sub>C<sub>2</sub>T<sub>x</sub> composite.</p>\\n </li>\\n <li>\\n <p>Diagnosis of coronary heart disease was achieved with the help of machine learning.</p>\\n </li>\\n </ul>\\n </div></div>\",\"PeriodicalId\":714,\"journal\":{\"name\":\"Nano-Micro Letters\",\"volume\":\"16 1\",\"pages\":\"\"},\"PeriodicalIF\":26.6000,\"publicationDate\":\"2024-08-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11327237/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nano-Micro Letters\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s40820-024-01481-7\",\"RegionNum\":1,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nano-Micro Letters","FirstCategoryId":"88","ListUrlMain":"https://link.springer.com/article/10.1007/s40820-024-01481-7","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Engineering","Score":null,"Total":0}

引用次数: 0

摘要

早期无创诊断冠心病（CHD）至关重要。然而，通过检测呼气来实现冠心病的准确诊断具有挑战性。在这项工作中，利用自组装策略配制了具有高气体灵敏度和光响应性的黑磷（BP）与二维碳化物和氮化物（MXene）的异质结构复合物。在光调节下制备了基于 BP/Ti3C2Tx 的光激活虚拟传感器阵列（LAVSA），并将其进一步组装成即时气体传感平台（IGSP）。此外，还引入了机器学习（ML）算法，帮助 IGSP 检测和识别呼气样本信号，以诊断心脏病。由于 BP 和 Ti3C2Tx 以及光激发的协同作用，合成的异质结构复合物比原始 Ti3C2Tx 表现出更高的性能，响应值比原始 Ti3C2Tx 高 26%。此外，在模式识别算法的帮助下，LAVSA 成功地检测和识别了 15 种气味分子，分别与醇、酮、醛、酯和酸有关。同时，在 ML 的帮助下，IGSP 对 45 名健康人和心脏病患者志愿者呼气气味的检测准确率达到了 69.2%。总之，我们设计并制造出了一种即时、低成本、准确的原型，用于无创诊断心脏病，为诊断其他疾病和其他更复杂的应用场景提供了通用解决方案。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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

查看原文本刊更多论文

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

Highlights

Photoresponsive black phosphorus (BP)/Ti₃C₂T_x 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/Ti₃C₂T_x composite.
Diagnosis of coronary heart disease was achieved with the help of machine learning.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Nano-Micro Letters NANOSCIENCE & NANOTECHNOLOGY-MATERIALS SCIENCE, MULTIDISCIPLINARY

CiteScore

32.60

自引率

4.90%

发文量

981

审稿时长

1.1 months

期刊介绍： Nano-Micro Letters is a peer-reviewed, international, interdisciplinary, and open-access journal published under the SpringerOpen brand. Nano-Micro Letters focuses on the science, experiments, engineering, technologies, and applications of nano- or microscale structures and systems in various fields such as physics, chemistry, biology, material science, and pharmacy.It also explores the expanding interfaces between these fields. Nano-Micro Letters particularly emphasizes the bottom-up approach in the length scale from nano to micro. This approach is crucial for achieving industrial applications in nanotechnology, as it involves the assembly, modification, and control of nanostructures on a microscale.