Helping Roles of Artificial Intelligence (AI) in the Screening and Evaluation of COVID-19 Based on the CT Images.

Objective: The aim of this study was to explore the role of the AI system which was designed and developed based on the characteristics of COVID-19 CT images in the screening and evaluation of COVID-19.

Methods: The research team adopted an improved U-shaped neural network to segment lungs and pneumonia lesions in CT images through multilayer convolution iterations. Then the appropriate 159 cases were selected to establish and train the model, and Dice loss function and Adam optimizer were used for network training with the initial learning rate of 0.

Upregulation of cervical carcinoma expressed PCNA regulatory long non-coding RNA promotes esophageal squamous cell carcinoma progression.

Cervical carcinoma expressed PCNA regulatory long non-coding (lnc)RNA (CCEPR) has recently been reported to play oncogenic roles in some common types of human cancer. However, the clinical significance of CCEPR mRNA expression levels in esophageal squamous cell carcinoma (ESCC) and the exact function of CCEPR in regulating the malignant phenotypes of ESCC cells have not been previously investigated. In the present study, CCEPR mRNA expression level was upregulated in ESCC tissues and cell lines, and overexpression of CCEPR was associated with advanced TNM stage, lymph node metastasis, and poor prognosis in ESCC.