Infectious Disease

COVID-19

Latest AI and machine learning research in covid-19 for healthcare professionals.

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Single-cell Multiome Analysis of Chromatin State and Transcriptome in the Human Basal Ganglia

The basal ganglia play essential roles in motor control, emotion, learning and reward processing. Th...

Prediction of Mutations and Outcome in Gastrointestinal Stromal Tumors with Deep Learning: A Multicenter, Multinational Study

Background: Gastrointestinal stromal tumor (GIST) is the most common gastrointestinal mesenchymal tu...

SLIM-Diff: Shared Latent Image-Mask Diffusion with Lp loss for Data-Scarce Epilepsy FLAIR MRI

Focal cortical dysplasia (FCD) lesions in epilepsy FLAIR MRI are subtle and scarce, making joint ima...

Lung Nodule Image Synthesis Driven by Two-Stage Generative Adversarial Networks

The limited sample size and insufficient diversity of lung nodule CT datasets severely restrict the ...

C-kNN-LSH: A Nearest-Neighbor Algorithm for Sequential Counterfactual Inference

Estimating causal effects from longitudinal trajectories is central to understanding the progression...

Data Augmentation for High-Fidelity Generation of CAR-T/NK Immunological Synapse Images

Chimeric antigen receptor (CAR)-T and NK cell immunotherapies have transformed cancer treatment, and...

Tissue-to-Analysis Framework Enables Multiscale Mapping of the Architectural and Cellular Organization in the Human Dorsal Root Ganglion

Transcriptomic studies have helped us understand the dorsal root ganglia's cellular milieu, yet our ...

Integrating multi-omic QTLs and predictive models reveals regulatory architectures at immune-related GWAS loci in CD4+ T cells

Functional interpretation is essential for understanding how genetic variants contribute to complex ...

A systematic assessment of machine learning for structural variant filtering

Background: Accurate discrimination of true structural variants (SVs) from artifacts in long-read se...

A Unified Study of LoRA Variants: Taxonomy, Review, Codebase, and Empirical Evaluation

Low-Rank Adaptation (LoRA) is a fundamental parameter-efficient fine-tuning method that balances eff...

Gene-centered representation of coding and regulatory variation enables outcome prediction

Integrating coding and regulatory variation into unified, interpretable representations remains a ch...

De novo design of a safe and potent respiratory syncytial virus immuno-focusing antigen

Respiratory syncytial virus (RSV) remains the leading cause of severe respiratory infections in infa...

Can Local Learning Match Self-Supervised Backpropagation?

While end-to-end self-supervised learning with backpropagation (global BP-SSL) has become central fo...

Machine Learning Method for Optimizing Coding Sequences in Mammalian Cells

Mammalian cell lines are the preferred hosts for producing commercially relevant therapeutic protein...

SemBind: Binding Diffusion Watermarks to Semantics Against Black-Box Forgery Attacks

Latent-based watermarks, integrated into the generation process of latent diffusion models (LDMs), s...

Demystifying Prediction Powered Inference

Machine learning predictions are increasingly used to supplement incomplete or costly-to-measure out...

A Clinical Theory-Driven Deep Learning Model for Interpretable Autism Severity Prediction

Autism spectrum disorder (ASD) affects a substantial proportion of children worldwide, yet clinical ...

Learning with Geometric Priors in U-Net Variants for Polyp Segmentation

Accurate and robust polyp segmentation is essential for early colorectal cancer detection and for co...

AlphaGenome -enabled analysis of non-coding regulatory variants underlying RHD Expression

Systematic identification of functional non-coding regulatory variants remains a major challenge in ...

TCRAD: An End-to-End Framework for Antigen-Targeted T Cell Receptor Design

Understanding and engineering T-cell receptor (TCR) specificity is central to personalized immunothe...

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