APPLICATION OF MACHINE LEARNING IN LUNG CANCER DETECTION

Currently, artificial intelligence is widely used in many fields. Artificial intelligence is also widely used in the field of medicine. This study used machine learning models to predict lung cancer. The study used a dataset consisting of lung cancer patients. Among the machine learning models used in the early detection of lung cancer are K-Neighbor Classifier, Support Vector Machine (SVM), Logistic Regression, Random Forest Classifier, Gradient Boosting Classifier, LGBM Classifier, and Support Vector Classifier. The prediction accuracies of these models were obtained, as a result, SVM and Support Vector Classifier models showed high performance of 99%, while other models such as K-Neighbor Classifier and Random Forest achieved high results ranging from 87.39% to 94.96%. The results show that machine learning models in lung cancer detection have shown superior results and have made a great contribution to future lung cancer detection and research in this field. The datasets and machine learning models used in the study have been proven to yield superior results when used in the medical field. In addition to the machine learning models considered in the study, it is recommended to use deep learning models in the future.