[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-366107-105":59,"doc-detail-366107-en":131},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":124,"head_meta":126,"extra_data":128,"updated_unix":130},105,"en","electronic-nose-and-lung-cancer-electronic-nose-technology-for-lung-cancer-detection-a-non-invasive-diagnostic-revolution","Electronic Nose and Lung Cancer - Electronic‑Nose Technology for Lung Cancer Detection: A Non‑Invasive Diagnostic Revolution","","Lung cancer remains a major cause of cancer-related mortality, especially when diagnosis occurs late and reliable early detection tools are limited. This review examines electronic nose systems for early lung cancer screening by outlining operating principles, recent technological progress, and practical constraints. It synthesizes evidence from studies using exhaled-breath volatile organic compounds, while emphasizing AI- and machine-learning-based pattern recognition. Key barriers include sensor stability, inconsistent breath collection, demographic effects, and the need for large training datasets for robust clinical translation.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/electronic-nose-and-lung-cancer-electronic-nose-technology-for-lung-cancer-detection-a-non-invasive-diagnostic-revolution/366107/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/electronic-nose-and-lung-cancer-electronic-nose-technology-for-lung-cancer-detection-a-non-invasive-diagnostic-revolution/366107.png","ImageObject",300,407,{"name":92,"@type":93},"Rizky","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-31","2026-09-23",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",12,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What problem does the review address in lung cancer screening?","Question",{"text":113,"@type":114},"It focuses on lung cancer’s high mortality linked to late-stage diagnosis and the lack of effective early detection methods.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"How do electronic nose systems support early lung cancer detection?",{"text":118,"@type":114},"They analyze volatile organic compounds in exhaled breath and use AI or machine learning to recognize patterns and classify samples.",{"name":120,"@type":111,"acceptedAnswer":121},"Why is clinical adoption of E-nose technology still limited?",{"text":122,"@type":114},"Challenges include sensor stability, lack of standardized breath-collection procedures, demographic variability, and the requirement for large training datasets for AI models.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},366107,1790823339,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":56,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145},962085564807,"https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8","Lung (2025) 203:76  \n[https://doi.org/10.1007/s00408-025-00828-0](https://doi.org/10.1007/s00408-025-00828-0)  \nREVIEW  \nELECTRONIC NOSE AND LUNG CANCER  \nElectronic‑Nose Technology for Lung Cancer Detection: A Non‑Invasive Diagnostic Revolution  \nA. M. Dhanush Gowda1 · Akanksha D. Dessai1 · UshaY. Nayak1  \nReceived: 30 April 2025 / Accepted: 12 June 2025 / Published online: 8 July 2025 © The Author(s) 2025  \nAbstract  \nBackground Lung cancer (LC) remains a leading cause of cancer-related mortality worldwide, primarily due to late-stage diagnosis and the absence of effective early detection methods.  \nObjective This review aims to explore the principles, technological advancements, current limitations, and future prospects of electronic nose (E-nose) systems in the early detection of lung cancer.  \nMethods The review analyzes recent literature on E-nose devices that detect volatile organic compounds (VOCs) in exhaled breath, focusing on their integration with artificial intelligence (AI) and machine learning for pattern recognition and diagnostic classification.  \nResults E-noses have demonstrated high sensitivity and specificity in differentiating cancerous from non-cancerous breath samples. However, challenges such as sensor stability, lack of standardization in breath collection, demographic variability, and the need for large training datasets for AI models limit their clinical adoption.  \nConclusion Despite current limitations, E-nose technology shows strong potential as a rapid, non-invasive, and cost-effective tool for early LC screening. Enhancing sensor durability, improving data processing, and conducting large-scale validation studies are critical next steps. Integration with imaging and molecular biomarkers may further improve diagnostic accuracy and clinical utility.  \n* Usha Y. Nayak [usha.nayak@manipal.edu](usha.nayak@manipal.edu)  \n1 Department of Pharmaceutics, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India  \nGraphical Abstract  \nKeywords E-nose · Lung cancer · Volatile organic compounds · Non-invasive · Lung cancer diagnosis  \nAbbreviations  \nLC Lung Cancer  \nVOC Volatile Organic Compounds  \nE-nose Electronic Nose  \nAI Artificial Intelligence  \nCT Computer-based Tomography  \nGC-MS Gas Chromatography-Mass Spectrometry NPV Negative Predictive Value  \nROS Reactive Oxygen Species  \nCYP450 Cytochrome P450  \nPUFA Poly-unsaturated Fatty Acids  \nMEMS Micro-Electro-Mechanical Systems  \nANN Artificial Neural Network  \nPCA Principal Component Analysis  \nSVM Support Vector Machine  \nMOS Metal Oxide Semiconductor  \nSnO₂ Stannic Oxide  \nZnO Zinc Oxide  \nWO₃ Tungsten Trioxide  \nTiO₂ Titanium Dioxide  \nSPR Surface Plasmon Resonance  \nBAW  \nSAW  \nPC  \nMOF  \nQCM  \nML  \nAUC  \nDSP  \nCNN  \nRNN  \nLSTM  \nSoC  \nNSCLC  \nSCLC  \nSCC  \nADC  \nCOPD  \nGC-FAIMS  \nKI  \nKNN  \nBulk Acoustic Wave  \nSurface Acoustic Wave Polycarbonate  \nMetal-Organic Framework Quartz Crystal Microbalance Machine Learning  \nArea Under Curve  \nDigital Signal Processor Convolutional Neural Network Recurrent Neural Network Long Short-Term Memory System-on-Chip  \nNon-Small Cell Lung Cancer Small Cell Lung Cancer Squamous Cell Carcinoma Adenocarcinoma  \nChronic Obstructive Pulmonary Disease Gas Chromatography—Field Asymmetric Ion Mobility Spectrometry  \nKovats Index  \nK-Nearest Neighbors  \nLDAWDELM  \nGA  \nXGBoost  \nLinear Discriminant Analysis  \nWeighted Discriminative Extreme Learning Machine  \nGenetic Algorithm  \nEXtreme Gradient Boosting  \nIntroduction to Electronic Nose  \nLung cancer (LC) is an aggressive and multifaceted disease and affects every patient differently. The disease grows quickly and can sometimes be challenging to treat, meaning that no case is alike from the next one [1] . According to GLOBOCAN 2020, there were approximately 2.2 million new cases of LC (11.4%) and nearly 1.8 million LCrelated deaths (18 .0%) in 2020 [2] . LC was the second most prevalent cancer diagnosis globally in","cbCaig5ZIBES0ri2","https://ap.wps.com/l/cbCaig5ZIBES0ri2","pdf",3436879,"English","# Abstract\n## Background\n## Objective\n## Methods\n## Results\n## Conclusion\n# Introduction to Electronic Nose\n## Lung cancer burden and need for early detection\n## Limitations of existing diagnostic techniques\n## Promise of electronic-nose as a non-invasive alternative","[{\"question\":\"What problem does the review address in lung cancer screening?\",\"answer\":\"It focuses on lung cancer’s high mortality linked to late-stage diagnosis and the lack of effective early detection methods.\"},{\"question\":\"How do electronic nose systems support early lung cancer detection?\",\"answer\":\"They analyze volatile organic compounds in exhaled breath and use AI or machine learning to recognize patterns and classify samples.\"},{\"question\":\"Why is clinical adoption of E-nose technology still limited?\",\"answer\":\"Challenges include sensor stability, lack of standardized breath-collection procedures, demographic variability, and the requirement for large training datasets for AI models.\"}]","Electronic Nose and Lung Cancer - Electronic‑Nose Technology for Lung Cancer Detection: A Non‑Invasive Diagnostic Revolution | PDF",1790163840,48]