Allergy & Immunology

Allergy

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

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Mapping and reprogramming human tissue microenvironments with MintFlow

Tissue microenvironments reprogram local cellular states in disease, yet current computational spati...

ATOMIC: A graph attention neural network for ATOpic dermatitis prediction on human gut MICrobiome

Atopic dermatitis (AD) is a chronic inflammatory skin disease driven by complex interactions among g...

Integrating explainable AI with multiomics systems biology and EHR data mining for personalized drug repurposing in Alzheimer’s disease

Alzheimer’s disease (AD) is characterized by region- and patient-specific molecular heterogeneity, w...

Quantum Convolutional HLA Immunogenic Peptide Prediction (Q-CHIPP): Next-Generation Neoantigen Prediction with Quantum Neural Networks

The immune system is an intricately evolved series of cellular and protein-protein interactions, whi...

Multivariate pattern analysis reveals resting-state EEG biomarkers in fibromyalgia

Fibromyalgia (FM) involves widespread musculoskeletal pain and hypersensitivity, often accompanied b...

CART-GPT: A T Cell-Informed AI Linguistic Framework for Interpreting Neurotoxicity and Therapeutic Outcomes in CAR-T Therapy

Chimeric antigen receptor (CAR) T cell therapy holds transformative potential for hematologic malign...

Reengineering the antigen optimization process for superior neoantigen vaccine design

Identifying effective neoantigen sequences is essential for enhancing anti-tumor immunity. However, ...

The hidden predictors of human haematopoietic clonal fate

Human haematopoietic stem and progenitor cells (HSPCs) exhibit heterogeneous lineage output, but the...

Translating clinical gene sequencing into a foundational representation of tumor subtype

While gene sequencing is routine in cancer care, translating sequences into treatment decisions rema...

SpaPheno: Linking Spatial Transcriptomics to Clinical Phenotypes with Interpretable Machine Learning

Linking spatial transcriptomic data to clinically relevant phenotypes is essential for advancing spa...

BLMPred: predicting linear B-cell epitopes using pre-trained protein language models and machine learning

B-cells get activated through interaction with B-cell epitopes, a specific portion of the antigen. I...

Fourier transform infrared spectroscopy enables rapid species discrimination across Malassezia and strain-level typing in M. pachydermatis

Malassezia pachydermatis is a zoophilic yeast found on the skin and in the outer ear canal of many m...

Accurate and scalable multi-disease classification from adaptive immune repertoires

Machine learning models trained on paratope-similarity networks have shown superior accuracy compare...

Iterative improvement of deep learning models using synthetic regulatory genomics

Deep learning models can accurately reconstruct genome-wide epigenetic tracks from the reference gen...

Tricked by Edge Cases: Can Current Approaches Lead to Accurate Prediction of T-Cell Specificity with Machine Learning?

The ability to predict T cell receptor (TCR) specificity from sequence could transform immunotherapy...

LoFT-TCR: A LoRA-based Fine-tuning Framework for TCR-Antigen Binding Prediction

T cells recognize and eliminate diseased cells by binding their T cell receptors (TCRs) to short end...

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