Development of a machine learning-based multimode diagnosis system for lung cancer.

ABSTRACT: As an emerging technology, artificial intelligence has been applied to identify various physical disorders. Here, we developed a three-layer diagnosis system for lung cancer, in which three machine learning approaches including decision tree C5.0, artificial neural network (ANN) and support vector machine (SVM) were involved. The area under the curve (AUC) was employed to evaluate their decision powers. In the first layer, the AUCs of C5.0, ANN and SVM were 0.676, 0.736 and 0.640, ANN was better than C5.0 and SVM. In the second layer, ANN was similar with SVM but superior to C5.0 supported by the AUCs of 0.804, 0.889 and 0.825. Much higher AUCs of 0.908, 0.910 and 0.849 were identified in the third layer, where the highest sensitivity of 94.12% was found in C5.0. These data proposed a thre

SUBMITTER: Duan S 

PROVIDER: S-EPMC7288961 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature