Allergy & Immunology

Allergy

Latest AI and machine learning research in allergy for healthcare professionals.

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Showing 1301-1320 of 10,996 articles

RS$^3$-Prune: Read-Sparse, Store-Sparse Token Pruning for Video Object Segmentation

We introduce RS$^3$-Prune, a training-free token-pruning recipe that instantiates as a small set of inference time hooks atop existing video object segmentation (VOS) networks. Modern VOS models have converged on a common, expensive design: an image encoder produces a dense token grid for every frame, and a memory bank accumulates these tokens across all previously processed frames to condition fu...

Aug 23 2026 2608.22526v1

A Multi-stage Precision Stratification (MPS) Framework for Navigating Adjuvant Immunotherapy in Hepatocellular Carcinoma After Resection

BackgroundRecurrence rates following curative resection for hepatocellular carcinoma (HCC) remain persistently high, benefit from adjuvant immunotherapy varies substantially across patients, and the field currently lacks a standardized framework to characterize the postoperative host immune contexture. PurposeTo propose and validate a Multi-stage Precision Stratification (MPS) framework and evalu...

PanoraOnc: A pan-cancer clinico-genomic AI model for transferable outcome predictions

Progress in precision oncology, including biomarker discovery and individualized treatment selection, is limited by the complexity of clinico-genomic ...

A Generative Virtual Tissue Model Enables Computational Design of Therapeutic Perturbation Strategies

Computational design has transformed many fields of engineering, where simulators can explore millions of candidate design configurations before exper...

Ensembles of in silico structures enable T cell peptide-MHC binding prediction

Adaptive immunity relies on T-cell receptor (TCR) recognition of peptides presented by the major histocompatibility complex (pMHC). Accurate predictio...

Deep learning representations of human Immune Health for precision immunology

The human immune system is composed of [~]30-50 distinct cell types, each of which can exist in different states of activation or differentiation. Ind...

Using binary silver labels in electronic health records-based computable phenotyping algorithms

Gold-standard phenotype labels are often unavailable at scale in electronic health record (EHR) studies because they require manual chart review. Weak...

Jul 20 2026 2607.18431v1
CAR T cell foundation model predicts immunotherapy response

Single-cell transcriptomics resolves CAR T-cell states, yet translating heterogeneous cellular signals into patient-level therapeutic response remains...

What Do Generative Models Learn About Adaptive Immune Receptor Repertoires? A Benchmark Study

Generative models are increasingly used to model adaptive immune receptor repertoire (AIRR) sequence distributions, promising to decode the sequence d...

Mechanistically informed adaptive dosing for cancer immunotherapy using AI-guided decision making

Optimizing dose and schedule remains a central challenge in oncology drug development, particularly for immunotherapies where fixed dosing regimens of...

Multimodal profiling for prediction of primary resistance to anti-PD-(L)1 therapy in advanced non-small-cell lung cancer: the prospective PIONeeR biomarkers study

Background Pretreatment prediction of primary resistance to anti-PD-(L)1 therapy in advanced non-small-cell lung cancer (NSCLC) remains an unmet clini...

Deciphering the Tumor Microenvironment: An Integrated Single-Cell RNA-Seq and AI Framework for Novel Biomarker and Therapeutic Target Discovery in Melanoma

Background: Melanoma represents a highly immunogenic and therapeutically challenging malignancy. The complex cellular ecosystem of the tumor microenvi...

Effects of gabapentin on ongoing behaviors displayed by mice with chemotherapy neuropathy

Chemotherapy-induced peripheral neuropathy (CIPN) is a common and painful side effect of paclitaxel (PTX) treatment. The most common measures of painf...

Identifying anaphylaxis using weakly-supervised prediction models and natural language processing

Objectives Scalable computable phenotyping algorithms are critical for conducting high-throughput disease-outcome research in large, distributed-data ...

Million-scale multimodal pollen microscopy with expert-guided foundation models

Automated pollen identification from microscopy remains a bottleneck in aerobiology, palaeoecology and biodiversity monitoring, because scalable syste...

Jun 16 2026 2606.17809v1
Generative design of antigen-specific T-cell receptor sequences with a conditional diffusion model

T cell receptor (TCR)-based immunotherapy holds immense potential for treating cancers and infectious diseases, where highly antigen-specific TCR reco...

DyMoTree decodes early cell state transitions and drivers from single-cell transcriptomes using a tree-structured neural network

Inferring early cell fate from single-cell RNA-sequencing data is essential for identifying cellular origins and fate plasticity in development and di...

MHC Attention: Identifying HLA-E presented cancer antigens through deep learning and high-throughput screening

HLA-E presented cancer peptides can be promising cancer therapy targets, as HLA-E is minimally polymorphic and widely expressed across human populatio...

HSSM: A Widely Applicable Toolbox for Hierarchical Bayesian Neuro-cognitive Modeling

Computational models are central to cognitive neuroscience, but their rigorous application to experimental datasets is often constrained to a narrow s...

Patient-Level Diagnosis of Acute Myeloid Leukemia via Deep Learning Analysis of Bone Marrow Smear

Bone marrow smear review remains important for acute myeloid leukemia (AML) assessment, but manual single-cell interpretation is labor-intensive and p...

Jun 9 2026 2606.10735v1
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