[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-332858-105":3,"detail-sidebar-cat-0-en-105":81,"doc-detail-332858-en":130},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":74,"head_meta":76,"extra_data":78,"updated_unix":80},105,"en","exploring-components-sensors-and-techniques-for-cancer-detection-via-enose-technology-a-systematic-review","Exploring Components, Sensors, and Techniques for Cancer Detection via eNose Technology - A Systematic Review","","This paper provides a systematic review of advances in electronic nose (eNose) technologies for early cancer detection, emphasizing detection and analysis of volatile organic compounds (VOCs) in biomarkers from breath, urine, saliva, and blood. The review analyzes 120 studies published between 2018 and 2023 using systematic mapping and literature review methods guided by PICOS (Population, Intervention, Comparison, Outcome, and Study design). Included work highlights technical and clinical evaluations of sensor-based devices such as GC–MS and SIFT–MS, with frequent use of machine-learning techniques including SVM, PCA, and ANN.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & Report",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/exploring-components-sensors-and-techniques-for-cancer-detection-via-enose-technology-a-systematic-review/332858/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/exploring-components-sensors-and-techniques-for-cancer-detection-via-enose-technology-a-systematic-review/332858.png","ImageObject",300,407,{"name":42,"@type":43},"Clementine","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-28","2026-09-21",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",6,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What is the main focus of the systematic review on eNose technology?","Question",{"text":63,"@type":64},"The review focuses on electronic nose technologies for early cancer detection by detecting and analyzing volatile organic compounds (VOCs) in biomarkers such as breath, urine, saliva, and blood.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"How many studies were examined, and what time range did they cover?",{"text":68,"@type":64},"A total of 120 studies published between 2018 and 2023 were examined using systematic mapping and literature review methodologies.",{"name":70,"@type":61,"acceptedAnswer":71},"Which analytical techniques and machine-learning methods were most frequently used?",{"text":72,"@type":64},"The review identifies Support Vector Machine (SVM), Principal Component Analysis (PCA), and Artificial Neural Networks (ANN) as the most prevalent analytical techniques across the included studies.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},332858,1790193739,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,105,110,114,119,122,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":97,"doc_module":4,"doc_module_name":25,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":55,"doc_module":4,"doc_module_name":25,"category_name":102,"show_sort_weight":103,"slug":104},"Technology",50,"technology",{"id":106,"doc_module":4,"doc_module_name":25,"category_name":107,"show_sort_weight":108,"slug":109},7,"Healthcare",40,"healthcare",{"id":111,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":112,"slug":113},8,30,"research-report",{"id":115,"doc_module":4,"doc_module_name":25,"category_name":116,"show_sort_weight":117,"slug":118},9,"Religion & Spirituality",20,"religion-spirituality",{"id":117,"doc_module":4,"doc_module_name":25,"category_name":120,"show_sort_weight":117,"slug":121},"World Cup","world-cup",{"id":123,"doc_module":4,"doc_module_name":25,"category_name":124,"show_sort_weight":123,"slug":125},10,"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":25,"category_name":128,"show_sort_weight":97,"slug":129},19,"General","general",{"code":4,"msg":82,"data":131},{"doc_id":79,"user_id":132,"nickname":42,"user_avatar":133,"doc_module":4,"category_id":111,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":139,"language":140,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":12,"update_tm":144,"read_time":145,"preview_page_count":4},1374391974564,"https://ap-avatar.wpscdn.com/avatar/14000253aa45c000a9e?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779874745381141002","Review  \nExploring Components, Sensors, and Techniques for Cancer Detection via eNose Technology: A Systematic Review  \nWashington Ramírez 1, *, Verónica Pillajo 2, Eileen Ramírez 3, *, Ibeth Manzano 1 and Doris Meza 4  \nCitation: Ramírez, W.; Pillajo, V.; Ramírez, E.; Manzano, I.; Meza, D. Exploring Components, Sensors, and Techniques for Cancer Detection viaeNose Technology: A Systematic Review. Sensors 2024, 24, 7868 . [https://doi.org/10.3390/s24237868](https://doi.org/10.3390/s24237868)  \nAcademic Editor: Jun Wang  \nReceived: 10 October 2024  \nRevised: 25 November 2024  \nAccepted: 27 November 2024  \nPublished: 9 December 2024  \nCopyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([https://](https://)[ ](https://)[creativecommons.org/licenses/by/](creativecommons.org/licenses/by/)[ ](creativecommons.org/licenses/by/)[4.0/](4.0/)) .  \n1 Departamento de Ciencias de la Computación, Universidad de las Fuerzas Armadas ESPE, Av. Gral.  \nRumiñahui S/N, Sangolquí 171104, Ecuador; [iamanzano@espe.edu.ec](iamanzano@espe.edu.ec)  \n2 Departamento de Informática, Universidad Politécnica Salesiana, Quito 170146, Ecuador; [vpillajon@est.ups.edu.ec](vpillajon@est.ups.edu.ec)  \n3 Facultad de Medicina, Pontificia Universidad Católica del Ecuador, Quito 170143, Ecuador  \n4 Facultad de Ciencias Económicas, Universidad Central del Ecuador, Quito 170521, Ecuador; [dmeza@uce.edu.ec](dmeza@uce.edu.ec)  \n* [Correspondence: waramirez3@espe.edu.ec](Correspondence: waramirez3@espe.edu.ec) (W.R.); [edramirez@puce.edu.ec](edramirez@puce.edu.ec) (E.R.)  \nAbstract: This paper offers a systematic review of advancements in electronic nose technologies for early cancer detection with a particular focus on the detection and analysis of volatile organic compounds present in biomarkers such as breath, urine, saliva, and blood. Our objective is to comprehensively explore how these biomarkers can serve as early indicators of various cancers, enhancing diagnostic precision and reducing invasiveness. A total of 120 studies published between 2018 and 2023 were examined through systematic mapping and literature review methodologies, employing the PICOS (Population, Intervention, Comparison, Outcome, and Study design) methodology to guide the analysis. Of these studies, 65.83% were ranked in Q1 journals, illustrating the scientific rigor of the included research. Our review synthesizes both technical and clinical perspectives, evaluating sensor-based devices such as gas chromatography–mass spectrometry and selected ion flow tube–mass spectrometry with reported incidences of 30 and 8 studies, respectively. Key analytical techniques including Support Vector Machine, Principal Component Analysis, and Artificial Neural Networks were identified as the most prevalent, appearing in 22, 24, and 13 studies, respectively. While substantial improvements in detection accuracy and sensitivity are noted, significant challenges persist in sensor optimization, data integration, and adaptation into clinical settings. This comprehensive analysis bridges existing research gaps and lays a foundation for the development of non-invasive diagnostic devices. By refining detection technologies and advancing clinical applications, this work has the potential to transform cancer diagnostics, offering higher precision and reduced reliance on invasive procedures. Our aim is to provide a robust knowledge base for researchers at all experience levels, presenting insights on sensor capabilities, metrics, analytical methodologies, and the transformative impact of emerging electronic nose technologies in clinical practice.  \nKeywords: cancer detection; eNose; biomarkers; components; sensors; machine learning techniques; medical devices; Support Vector Machine; Principal Component Analysis; systematic review  \n1. Introduction  \nEarly cancer detection re","cbCaig3ILjOenfo6","https://ap.wps.com/l/cbCaig3ILjOenfo6","pdf",2949984,68,"English","# Introduction\n## Electronic nose technology and VOCs as biomarkers\n## Study scope and systematic review approach\n# Abstract\n## Review objectives and PICOS-based methodology\n## Study selection and device and technique evaluation\n# Keywords\n## Core concepts and methods","[{\"question\":\"What is the main focus of the systematic review on eNose technology?\",\"answer\":\"The review focuses on electronic nose technologies for early cancer detection by detecting and analyzing volatile organic compounds (VOCs) in biomarkers such as breath, urine, saliva, and blood.\"},{\"question\":\"How many studies were examined, and what time range did they cover?\",\"answer\":\"A total of 120 studies published between 2018 and 2023 were examined using systematic mapping and literature review methodologies.\"},{\"question\":\"Which analytical techniques and machine-learning methods were most frequently used?\",\"answer\":\"The review identifies Support Vector Machine (SVM), Principal Component Analysis (PCA), and Artificial Neural Networks (ANN) as the most prevalent analytical techniques across the included studies.\"}]","Exploring Components, Sensors, and Techniques for Cancer Detection via eNose Technology - A Systematic Review | PDF",1789999783,171]