Latest AI and machine learning research in covid-19 for healthcare professionals.
Antibodies exhibit extraordinary specificity and diversity in antigen recognition and have become a central class of therapeutics across a wide range of diseases. Despite this clinical success, antibody design remains fundamentally challenging. Antibody function emerges from intricate and highly coupled interactions between heavy and light chains, which complicate sequence-function relationships a...
3D editing has emerged as a critical research area to provide users with flexible control over 3D assets. While current editing approaches predominantly focus on 3D Gaussian Splatting or multi-view images, the direct editing of 3D meshes remains underexplored. Prior attempts, such as VoxHammer, rely on voxel-based representations that suffer from limited resolution and necessitate labor-intensive ...
Current autoregressive Vision Language Models (VLMs) usually rely on a large number of visual tokens to represent images, resulting in a need for more...
The basal ganglia play essential roles in motor control, emotion, learning and reward processing. Their dysfunction contributes to many neurological a...
Background: Gastrointestinal stromal tumor (GIST) is the most common gastrointestinal mesenchymal tumor, driven by tyrosine-protein kinase KIT and pla...
Focal cortical dysplasia (FCD) lesions in epilepsy FLAIR MRI are subtle and scarce, making joint image--mask generative modeling prone to instability ...
Foundation models aim to learn useful representations of biological sequences. However, the applicability of these representations for a wide range of...
The limited sample size and insufficient diversity of lung nodule CT datasets severely restrict the performance and generalization ability of detectio...
Estimating causal effects from longitudinal trajectories is central to understanding the progression of complex conditions and optimizing clinical dec...
Chimeric antigen receptor (CAR)-T and NK cell immunotherapies have transformed cancer treatment, and recent studies suggest that the quality of the CA...
Transcriptomic studies have helped us understand the dorsal root ganglia's cellular milieu, yet our knowledge of protein expression and spatial organi...
Functional interpretation is essential for understanding how genetic variants contribute to complex traits. Here, we identified and characterized regu...
Background: Accurate discrimination of true structural variants (SVs) from artifacts in long-read sequencing data remains a critical bottleneck. Numer...
Low-Rank Adaptation (LoRA) is a fundamental parameter-efficient fine-tuning method that balances efficiency and performance in large-scale neural netw...
Integrating coding and regulatory variation into unified, interpretable representations remains a challenge in functional genomics. Current approaches...
Respiratory syncytial virus (RSV) remains the leading cause of severe respiratory infections in infants, the elderly, and the immunocompromised. Altho...
While end-to-end self-supervised learning with backpropagation (global BP-SSL) has become central for training modern AI systems, theories of local se...
Mammalian cell lines are the preferred hosts for producing commercially relevant therapeutic proteins such as antibodies, multispecifics, and cytokine...
Latent-based watermarks, integrated into the generation process of latent diffusion models (LDMs), simplify detection and attribution of generated ima...
Machine learning predictions are increasingly used to supplement incomplete or costly-to-measure outcomes in fields such as biomedical research, envir...