OBJECTIVES: The objective of our study was to develop a nomogram to predict post-transjugular intrahepatic portosystemic shunt (TIPS) survival in patients with cirrhosis based on CT images.
OBJECTIVE: This study aimed to develop an automated method for segmenting spleen computed tomography (CT) images using a deep learning model to address the limitations of manual segmentation, which is known to be susceptible to inter-observer variabi...
Technology in cancer research & treatment
Jan 1, 2024
BACKGROUND: Breast cancer is a prevalent public health concern affecting numerous women globally and is associated with palmitoylation, a post-translational protein modification. Despite increasing focus on palmitoylation, its specific implications f...
Endocrine, metabolic & immune disorders drug targets
Jan 1, 2024
OBJECTIVE: To investigate and validate ferroptosis genes (FRGs) in ulcerative colitis (UC) for diagnostic, subtype, and biological agent reactivity, with the goal of providing a foundation for the identification of novel therapeutic targets and the r...
Technology in cancer research & treatment
Jan 1, 2023
Axillary lymph node (ALN) metastatic load is very important in the diagnosis and treatment of breast cancer (BC). We aimed to construct a model for predicting ALN metastatic load using deep learning radiomics (DLR) techniques based on the preoperati...
In the Cox proportional hazards regression model, which is the most commonly used model in survival analysis, the effects of independent variables on survival may not be constant over time and proportionality cannot be achieved, especially when long-...
BACKGROUND: The purpose of this study was to create a nomogram using machine learning models predicting risk of breast reconstruction complications with or without postmastectomy radiation therapy.
OBJECTIVE: We aimed to develop a deep learning-based signature to predict prognosis and benefit from adjuvant chemotherapy using preoperative computed tomography (CT) images.
Mathematical biosciences and engineering : MBE
Jul 16, 2021
The purpose of this study was to explore whether the Nomogram, which was constructed by combining the Deep learning and Radiomic features of T2-weighted MR images with Clinical factors (NDRC), could accurately predict placenta invasion. This retrospe...