An Effective Method for Lung Cancer Diagnosis from CT Scan Using Deep Learning-Based Support Vector Network.

ABSTRACT: The diagnosis of early-stage lung cancer is challenging due to its asymptomatic nature, especially given the repeated radiation exposure and high cost of computed tomography(CT). Examining the lung CT images to detect pulmonary nodules, especially the cell lung cancer lesions, is also tedious and prone to errors even by a specialist. This study proposes a cancer diagnostic model based on a deep learning-enabled support vector machine (SVM). The proposed computer-aided design (CAD) model identifies the physiological and pathological changes in the soft tissues of the cross-section in lung cancer lesions. The model is first trained to recognize lung cancer by measuring and comparing the selected profile values in CT images obtained from patients and control patients at their diagnosis. Then,

SUBMITTER: Shafi I 

PROVIDER: S-EPMC9657078 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature