Neusoft (China)

Hybrid Graph Neural Network Ensemble with Stacked Meta-Learning for Laboratory-Conditioned Chromatographic Retention-Time Prediction

Abstract Accurate prediction of chromatographic retention time (RT) is valuable for compound identification in untargeted metabolomics and forensic toxicology, yet validation must account for repeated molecular structures, chemical-space coverage, and heterogeneous laboratory sou...

Transformer‐Based Multitask Framework Integrating Habitat and Deep Learning for Predicting Early Disease Control and Survival in Immunotherapy‐Treated Hepatocellular Carcinoma

ABSTRACT Hepatocellular carcinoma (HCC) patients show heterogeneous responses to immune checkpoint inhibitors (ICIs). This study developed ECOS‐Net, a transformer‐based multitask network integrating CT‐derived habitat and 2.5‐dimensional (2.5D) deep learning features for simultan...

High–spatiotemporal resolution deuterium metabolic imaging enables in vivo phenotyping of intra- and intertumoral heterogeneity

Intra- and intertumoral heterogeneities raise fundamental biological questions and have important implications for accurate cancer diagnosis, prognosis, and treatment. These heterogeneities reflect tumor complexity, including a pronounced diversity in metabolic phenotypes and pro...

Multiomics Insights Into AL Amyloidosis

ABSTRACT Light chain amyloidosis is a systemic or localized protein conformational disorder triggered by misfolded immunoglobulin light chains, leading to amyloid fibril deposition. The disease is characterized by multiorgan involvement and delayed diagnosis, contributing to poor...