Resumen
Human-exhaled volatile organic compounds (VOCs) can be altered by lung cancer and become identifiable biomarkers. We used selected ion flow tube mass spectrometry (SIFT-MS) to quantitatively analyze 116 kinds of VOCs, which were exhaled by 148 lung cancer patients and 168 healthy individuals and collected from the environment to obtain a group of comprehensive data. A predictive model yielding 0.92 accuracy, 0.96 sensitivity, 0.88 specificity, and 0.98 area under the curve (AUC) was established using an advanced machine learning eXtreme Gradient Boosting (XGBoost) algorithm that considered the influences of exhaled and environmental VOCs.