Application of random survival forest to establish a nomogram combining clinlabomics-score and clinical data for predicting brain metastasis in primary lung cancer.

Purpose: To establish a nomogram for predicting brain metastasis (BM) in primary lung cancer at 12, 18, and 24 months after initial diagnosis.

Methods: In this study, we included 428 patients who were diagnosed with primary lung cancer at Harbin Medical University Cancer Hospital between January 2020 and January 2022. The endpoint event was BM.

Combination of DCE-MRI and NME-DWI via Deep Neural Network for Predicting Breast Cancer Molecular Subtypes.

Background: To explore whether the combination of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and nonmono-exponential (NME) model-based diffusion-weighted imaging (DWI) via deep neural network (DNN) can improve the prediction of breast cancer molecular subtypes compared to either imaging technique used alone.

Patients And Methods: This prospective study examined 480 breast cancers in 475 patients undergoing DCE-MRI and NME-DWI at 3.0 T.

In-situ synthesis of polypyrrole/silver for fabricating alginate fabrics with high conductivity, UV resistance and hydrophobicity.

In this research, the polypyrrole/silver (PPy/Ag) composite was first in-situ prepared on alginate fabrics by chemical oxidative polymerization of pyrrole (Py) monomer using silver nitrate as oxidant and sodium dodecyl sulfate (SDS) as the dopant. The effects of mole ratio of Py to silver nitrate, reaction time and dopant concentration on the preparation of PPy/Ag composite were optimized. It was found the optimal molar ratio of Py to silver nitrate was 1:1.