Lung cancer is one of the malignant tumor diseases with the fastest increase in morbidity
and mortality, which poses a great threat to human health. Low-Dose Computed …

Naive Bayesian classification algorithm is widely used in big data analysis and other fields
because of its simple and fast algorithm structure. Aiming at the shortcomings of the naive …

Differentiation between transient osteoporosis (TOH) and avascular necrosis (AVN) of the
hip is a longstanding challenge in musculoskeletal radiology. The purpose of this study was …

Objective Analysis of textural features of pulmonary nodules in chest CT, also known as
radiomics, has several potential clinical applications, such as diagnosis, prognostication …

With the deepening of people's research on event anaphora, a large number of methods will
be used in the identification and resolution of event anaphora. Although there has been …

Objective: To develop a Bayesian inversion framework on longitudinal chest CT scans which
can perform efficient multi-class classification of lung cancer. Methods: While the …

In Radiomics, deep learning-based systems for medical image analysis play an increasing
role. However, due to the better explainability, feature-based systems are still preferred …

Background Gallbladder carcinoma (GBC) is highly malignant, and its early diagnosis
remains difficult. This study aimed to develop a deep learning model based on contrast …

In view of the deficiency of naive Bayesian classifier in the assumption of attribute
independence, this paper constructs AdaBoost-naive Bayesian classification model to …