Detection of lung cancer in exhaled breath with an electronic nose using support vector machine analysis
Lung cancer is one of the most common malignancies and has a low 5-year survival rate. There are no
cheap, simple and widely available screening methods for the early diagnostics of lung cancer. The
aim of this study was to determine whether analysis of exhaled breath with an artificial olfactory
sensor using support vector analysis can differentiate patients with lung cancer from healthy
individuals and patients with other lung diseases, regardless of the stage of lung cancer and the
most common comorbidities. Patients with histologically or cytologically verified lung cancer,
healthy volunteers and patients with other lung diseases (e.g. chronic obstructive pulmonary disease
(COPD), asthma, pneumonia, pulmonary embolism, benign lung tumors) were enrolled in the study.
Breath sample collection and analysis with a Cyranose 320 sensor device was performed and data were
further analyzed using a support vector machine (SVM). The SVM correctly differentiated between
cancer patients ...
Source: Journal of Breath Research - Category: Respiratory Medicine Authors: Madara Tirz īte, Māris Bukovskis, Gunta Strazda, Normunds Jurka and Immanuels Taivans Source Type: research
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