Multigroup prediction in lung cancer patients and comparative controls using signature of volatile organic compounds in breath samples.

ABSTRACT: Early detection of lung cancer is a crucial factor for increasing its survival rates among the detected patients. The presence of carbonyl volatile organic compounds (VOCs) in exhaled breath can play a vital role in early detection of lung cancer. Identifying these VOC markers in breath samples through innovative statistical and machine learning techniques is an important task in lung cancer research. Therefore, we proposed an experimental approach for generation of VOC molecular concentration data using unique silicon microreactor technology and further identification and characterization of key relevant VOCs important for lung cancer detection through statistical and machine learning algorithms. We reported several informative VOCs and tested their effectiveness in multi-group classifica

SUBMITTER: Rai SN 

PROVIDER: S-EPMC9710764 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature