Diagnosis of lung cancer with E-nose

In this work an Electronic Nose system with low cost is developed in order to analyze human breath and this system's success is tested on diagnosing lung cancer. In this Electronic Nose system, Quartz Crystal Microbalance and Metal Oxide Semiconductor gas sensors are used. The sensors that are sensed to volatile organic compounds found in the breaths of patient lung cancer patients are selected. Breath examples of lung cancer patient and healthy people are analysed with this system. Data acquired from system are preprocessed and dimension of these data are reduced by Principal Component Analysis method. After this processed, features from data are extracted. Classification of data is examined with k-Nearest Neighbors, Support Vector Machines and Artificial Neural Networks algorithms. Maximum success rates obtained with these algorithms are 91.4%, 85.7%, 91.4% respectively.