{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T09:40:22Z","timestamp":1778319622976,"version":"3.51.4"},"reference-count":49,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2017,2,4]],"date-time":"2017-02-04T00:00:00Z","timestamp":1486166400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Monitoring exhaled breath is a very attractive, noninvasive screening technique for early diagnosis of diseases, especially lung cancer. However, the technique provides insufficient accuracy because the exhaled air has many crucial volatile organic compounds (VOCs) at very low concentrations (ppb level). We analyzed the breath exhaled by lung cancer patients and healthy subjects (controls) using gas chromatography\/mass spectrometry (GC\/MS), and performed a subsequent statistical analysis to diagnose lung cancer based on the combination of multiple lung cancer-related VOCs. We detected 68 VOCs as marker species using GC\/MS analysis. We reduced the number of VOCs and used support vector machine (SVM) algorithm to classify the samples. We observed that a combination of five VOCs (CHN, methanol, CH3CN, isoprene, 1-propanol) is sufficient for 89.0% screening accuracy, and hence, it can be used for the design and development of a desktop GC-sensor analysis system for lung cancer.<\/jats:p>","DOI":"10.3390\/s17020287","type":"journal-article","created":{"date-parts":[[2017,2,6]],"date-time":"2017-02-06T11:29:27Z","timestamp":1486380567000},"page":"287","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":103,"title":["Diagnosis by Volatile Organic Compounds in Exhaled Breath from Lung Cancer Patients Using Support Vector Machine Algorithm"],"prefix":"10.3390","volume":"17","author":[{"given":"Yuichi","family":"Sakumura","sequence":"first","affiliation":[{"name":"Department of Information Science and Technology, Aichi Prefectural University, Nagakute 480-1198, Japan"}]},{"given":"Yutaro","family":"Koyama","sequence":"additional","affiliation":[{"name":"Department of Information Science and Technology, Aichi Prefectural University, Nagakute 480-1198, Japan"}]},{"given":"Hiroaki","family":"Tokutake","sequence":"additional","affiliation":[{"name":"Department of Information Science and Technology, Aichi Prefectural University, Nagakute 480-1198, Japan"}]},{"given":"Toyoaki","family":"Hida","sequence":"additional","affiliation":[{"name":"Department of Thoracic Oncology, Aichi Cancer Center, 1-1 Kanokoden, Chikusa-ku, Nagoya 464-8681, Japan"}]},{"given":"Kazuo","family":"Sato","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Aichi Institute of Technology, Toyota, 470-0392, Japan"}]},{"given":"Toshio","family":"Itoh","sequence":"additional","affiliation":[{"name":"Department of Materials and Chemistry, National Institute of Advanced Industrial Science and Technology (AIST), Shimo-Shidami, Moriyama-ku, Nagoya 463-8560, Japan"}]},{"given":"Takafumi","family":"Akamatsu","sequence":"additional","affiliation":[{"name":"Department of Materials and Chemistry, National Institute of Advanced Industrial Science and Technology (AIST), Shimo-Shidami, Moriyama-ku, Nagoya 463-8560, Japan"}]},{"given":"Woosuck","family":"Shin","sequence":"additional","affiliation":[{"name":"Department of Materials and Chemistry, National Institute of Advanced Industrial Science and Technology (AIST), Shimo-Shidami, Moriyama-ku, Nagoya 463-8560, Japan"}]}],"member":"1968","published-online":{"date-parts":[[2017,2,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1278","DOI":"10.1093\/clinchem\/31.8.1278","article-title":"Volatile organic compounds in exhaled air from patients with lung cancer","volume":"31","author":"Gordon","year":"1985","journal-title":"Clin. Chem."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/13547500110104233","article-title":"Biomarkers of some pulmonary diseases in exhaled breath","volume":"7","author":"Kharitonov","year":"2002","journal-title":"Biomarkers"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"72S","DOI":"10.1378\/chest.123.1_suppl.72S","article-title":"Screening for lung cancer: A review of the current literature","volume":"123","author":"Bach","year":"2003","journal-title":"Chest"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1016\/0016-5085(90)90818-L","article-title":"The diagnosis of small bowel bacterial overgrowth. Reliability of jejunal culture and inadequacy of breath hydrogen testing","volume":"98","author":"Corazza","year":"1990","journal-title":"Gastroenterology"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1930","DOI":"10.1016\/S0140-6736(98)07552-7","article-title":"Volatile organic compounds in breath as markers of lung cancer: A cross-sectional study","volume":"353","author":"Phillips","year":"1999","journal-title":"Lancet"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/j.ijms.2004.08.010","article-title":"Applications of breath gas analysis in medicine","volume":"239","author":"Amann","year":"2004","journal-title":"Int. J. Mass Spectrom."},{"key":"ref_7","unstructured":"Amann, A., and Smith, D. (2005). Breath Analysis for Clinical Diagnosis and Therapeutic Monitoring: (With CD-ROM), World Scientific."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1286","DOI":"10.1164\/rccm.200409-1184OC","article-title":"Detection of lung cancer by sensor array analyses of exhaled breath","volume":"171","author":"Machado","year":"2005","journal-title":"Am. J. Respir. Crit. Care Med."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.ijms.2007.05.012","article-title":"Lung cancer detection by proton transfer reaction mass-spectrometric analysis of human breath gas","volume":"265","author":"Wehinger","year":"2007","journal-title":"Int. J. Mass Spectrom."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"774","DOI":"10.1097\/JTO.0b013e31817c7439","article-title":"Analysis of volatile organic compounds in the exhaled breath for the diagnosis of lung cancer","volume":"3","author":"Mazzone","year":"2008","journal-title":"J. Thorac. Oncol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2663","DOI":"10.1002\/ijc.24970","article-title":"Breath gas aldehydes as biomarkers of lung cancer","volume":"126","author":"Fuchs","year":"2010","journal-title":"Int. J. Cancer"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"465","DOI":"10.3390\/metabo4020465","article-title":"Breath analysis in disease diagnosis: Methodological considerations and applications","volume":"4","author":"Lourenco","year":"2014","journal-title":"Metabolites"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2115","DOI":"10.1378\/chest.123.6.2115","article-title":"Detection of lung cancer with volatile markers in the breath","volume":"123","author":"Phillips","year":"2003","journal-title":"Chest J."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1209","DOI":"10.1016\/S0956-5663(03)00086-1","article-title":"Lung cancer identification by the analysis of breath by means of an array of non-selective gas sensors","volume":"18","author":"Macagnano","year":"2003","journal-title":"Biosens. Bioelectron."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"95","DOI":"10.3233\/CBM-2007-3204","article-title":"Prediction of lung cancer using volatile biomarkers in breath","volume":"3","author":"Phillips","year":"2007","journal-title":"Cancer Biomark."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"669","DOI":"10.1038\/nnano.2009.235","article-title":"Diagnosing lung cancer in exhaled breath using gold nanoparticles","volume":"4","author":"Peng","year":"2009","journal-title":"Nat. Nanotechnol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.lungcan.2008.08.008","article-title":"An electronic nose in the discrimination of patients with non-small cell lung cancer and COPD","volume":"64","author":"Dragonieri","year":"2009","journal-title":"Lung Cancer"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1097\/JTO.0b013e318233d80f","article-title":"Exhaled breath analysis with a colorimetric sensor array for the identification and characterization of lung cancer","volume":"7","author":"Mazzone","year":"2012","journal-title":"J. Thorac. Oncol."},{"key":"ref_19","unstructured":"Pennazza, G., Santonico, M., Martinelli, E., D\u2019Amico, A., and Di Natale, C. (2010). Exhaled Biomarkers, European Respiratory Society."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"565","DOI":"10.1136\/thx.2006.072892","article-title":"Diagnosis of lung cancer by the analysis of exhaled breath with a colorimetric sensor array","volume":"62","author":"Mazzone","year":"2007","journal-title":"Thorax"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/j.cca.2008.02.021","article-title":"Detection of lung cancer using weighted digital analysis of breath biomarkers","volume":"393","author":"Phillips","year":"2008","journal-title":"Clin. Chim. Acta"},{"key":"ref_22","first-page":"774","article-title":"Pattern recognition using generalized portrait method","volume":"24","author":"Vapnik","year":"1963","journal-title":"Autom. Remote Control"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Ruan, S., Lebonvallet, S., Merabet, A., and Constans, J.-M. (2007, January 12\u201315). Tumor segmentation from a multispectral MRI images by using support vector machine classification. Proceedings of the 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Arlington, VA, USA.","DOI":"10.1109\/ISBI.2007.357082"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1609","DOI":"10.1002\/mrm.22147","article-title":"Classification of brain tumor type and grade using MRI texture and shape in a machine learning scheme","volume":"62","author":"Zacharaki","year":"2009","journal-title":"Magn. Reson. Med."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1093\/brain\/awm319","article-title":"Automatic classification of MR scans in Alzheimer\u2019s disease","volume":"131","author":"Stonnington","year":"2008","journal-title":"Brain"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1725","DOI":"10.1016\/j.patrec.2013.04.014","article-title":"LVQ-SVM based CAD tool applied to structural MRI for the diagnosis of the Alzheimer\u2019s disease","volume":"34","author":"Ortiz","year":"2013","journal-title":"Pattern Recognit. Lett."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1507","DOI":"10.1097\/WNR.0b013e328310425e","article-title":"Neuroanatomy of verbal working memory as a diagnostic biomarker for depression","volume":"19","author":"Marquand","year":"2008","journal-title":"Neuroreport"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"809","DOI":"10.1016\/j.neuroimage.2010.05.023","article-title":"Machine learning classification with confidence: Application of transductive conformal predictors to MRI-based diagnostic and prognostic markers in depression","volume":"56","author":"Nouretdinov","year":"2011","journal-title":"Neuroimage"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1016\/j.nano.2011.10.001","article-title":"Classification of lung cancer histology by gold nanoparticle sensors","volume":"8","author":"Barash","year":"2012","journal-title":"Nanomedicine"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.jchromb.2007.11.008","article-title":"Development of accurate classification method based on the analysis of volatile organic compounds from human exhaled air","volume":"861","author":"Dallinga","year":"2008","journal-title":"J. Chromatogr. B"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1016\/j.rmed.2009.10.018","article-title":"A profile of volatile organic compounds in breath discriminates COPD patients from controls","volume":"104","author":"Dallinga","year":"2010","journal-title":"Respir. Med."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1649","DOI":"10.1038\/bjc.2011.128","article-title":"Diagnosis of head-and-neck cancer from exhaled breath","volume":"104","author":"Hakim","year":"2011","journal-title":"Br. J. Cancer"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1891","DOI":"10.3390\/s16111891","article-title":"Development of an Exhaled Breath Monitoring System with Semiconductive Gas Sensors, a Gas Condenser Unit, and Gas Chromatograph Columns","volume":"16","author":"Itoh","year":"2016","journal-title":"Sensors"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1613\/jair.953","article-title":"SMOTE: Synthetic minority over-sampling technique","volume":"16","author":"Chawla","year":"2002","journal-title":"J. Artif. Intell. Res."},{"key":"ref_35","unstructured":"Akbani, R., Kwek, S., and Japkowicz, N. (2004). Machine Learning: ECML 2004, Proceedings of the 15th European Conference on Machine Learning, Pisa, Italy, 20\u201324 September 2004, Springer."},{"key":"ref_36","unstructured":"Chawla, N.V. (2005). Data Mining and Knowledge Discovery Handbook, Springer."},{"key":"ref_37","unstructured":"Bernhard, E.B., Isabelle, M.G., and Vapnik, V.N. (1992, January 27\u201329). A training algorithm for optimal margin classifiers. Proceedings of the Fifth Annual Workshop on Computational Learning Theory, Pittsburgh, PA, USA."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"906","DOI":"10.1093\/bioinformatics\/16.10.906","article-title":"Support vector machine classification and validation of cancer tissue samples using microarray expression data","volume":"16","author":"Furey","year":"2000","journal-title":"Bioinformatics"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1073\/pnas.97.1.262","article-title":"Knowledge-based analysis of microarray gene expression data by using support vector machines","volume":"97","author":"Brown","year":"2000","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_40","unstructured":"Chai, H., and Domeniconi, C. (2004, January 20\u201324). An evaluation of gene selection methods for multi-class microarray data classification. Proceedings of the Second European Workshop on Data Mining and Text Mining in Bioinformatics, Pisa, Italy."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1038\/nmeth976","article-title":"Accurate phylogenetic classification of variable-length DNA fragments","volume":"4","author":"McHardy","year":"2007","journal-title":"Nat. Methods"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"860","DOI":"10.1038\/ncb2764","article-title":"A screen for morphological complexity identifies regulators of switch-like transitions between discrete cell shapes","volume":"15","author":"Yin","year":"2013","journal-title":"Nat. Cell Biol."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"530","DOI":"10.1038\/415530a","article-title":"Gene expression profiling predicts clinical outcome of breast cancer","volume":"415","author":"Dai","year":"2002","journal-title":"Nature"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"6562","DOI":"10.1073\/pnas.102102699","article-title":"Selection bias in gene extraction on the basis of microarray gene-expression data","volume":"99","author":"Ambroise","year":"2002","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.tube.2006.03.004","article-title":"Volatile biomarkers of pulmonary tuberculosis in the breath","volume":"87","author":"Phillips","year":"2007","journal-title":"Tuberculosis"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1076","DOI":"10.1164\/rccm.200906-0939OC","article-title":"Exhaled breath profiling enables discrimination of chronic obstructive pulmonary disease and asthma","volume":"180","author":"Fens","year":"2009","journal-title":"Am. J. Respir. Crit. Care Med."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Gilad-Bachrach, R., Navot, A., and Tishby, N. (2004, January 4\u20138). Margin based feature selection-theory and algorithms. Proceedings of the Twenty-First International Conference on Machine Learning, Banff, AB, Canada.","DOI":"10.1145\/1015330.1015352"},{"key":"ref_48","first-page":"995","article-title":"Nearest neighbor based feature selection for regression and its application to neural activity","volume":"18","author":"Navot","year":"2006","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1016\/j.neuroimage.2011.11.002","article-title":"Diagnostic neuroimaging across diseases","volume":"61","author":"Abdulkadir","year":"2012","journal-title":"Neuroimage"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/2\/287\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:27:25Z","timestamp":1760207245000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/2\/287"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,2,4]]},"references-count":49,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2017,2]]}},"alternative-id":["s17020287"],"URL":"https:\/\/doi.org\/10.3390\/s17020287","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,2,4]]}}}