Allergy & Immunology

Breakthroughs and challenges of organoid models for assessing cancer immunotherapy: a cutting-edge tool for advancing personalised treatments.

Organoid models are powerful tools for evaluating cancer immunotherapy that provide a more accurate ...

Identification of pyroptosis-related gene S100A12 as a potential diagnostic biomarker for sepsis through bioinformatics analysis and machine learning.

Sepsis is a non-discriminatory inflammatory reaction that can result in a diverse array of organ dys...

PeruFoodNet: A unique dataset of traditional peruvian food for image recognition systems and allergenic ingredient inference.

Peruvian cuisine has won numerous international awards, attracting tourists from around the world to...

Interpretable machine learning algorithms reveal gut microbiome features associated with atopic dermatitis.

BACKGROUND: The "gut-skin axis" has been proposed to play an important role in the development and s...

Machine Learning-Driven Identification of Hematological and Immunological Biomarkers for Predicting Proliferative Diabetic Retinopathy Progression.

PURPOSE: Proliferative Diabetic Retinopathy (PDR) is a severe complication of diabetes characterized...

Tumor grade-titude: XGBoost radiomics paves the way for RCC classification.

This study aimed to develop and evaluate a non-invasive XGBoost-based machine learning model using r...

Artificial intelligence networks for assessing the prognosis of gastrointestinal cancer to immunotherapy based on genetic mutation features: a systematic review and meta-analysis.

BACKGROUND AND AIM: Artificial intelligence (AI) networks offer significant potential for predicting...

Protein interactions, network pharmacology, and machine learning work together to predict genes linked to mitochondrial dysfunction in hypertrophic cardiomyopathy.

This study looked at possible targets for hypertrophic cardiomyopathy (HCM), a condition marked by t...

Managing chronic disease in the digital era: The role of telemedicine apps and platforms.

Chronic diseases such as diabetes, heart disease, or asthma are one of the biggest health challenges...

Machine learning analysis of FOSL2 and RHoBTB1 as central immunological regulators in knee osteoarthritis synovium.

BackgroundKnee osteoarthritis is a debilitating disease with a complex pathogenesis. Synovitis, whic...

Altered static and dynamic functional network connectivity and combined Machine learning in asthma.

Asthma is a reversible disease characterized by airflow limitation and chronic airway inflammation. ...

Therapeutic potential of enzymes, neurosteroids, and synthetic steroids in neurodegenerative disorders: A critical review.

Neurodegenerative disorders present a significant challenge to healthcare systems, mainly due to the...

Can ChatGPT provide parent education for oral immunotherapy?

BACKGROUND: Oral Immunotherapy (OIT) has exhibited great potential in the treatment of food allergy....

Role of artificial intelligence in advancing immunology.

Artificial intelligence (AI) has revolutionized various biomedical fields, particularly immunology, ...

Pato: prediction of probiotic bacteria using metabolic features.

Probiotics have gained recognition for their health-promoting benefits, particularly in the gastroin...

Development and validation of a machine learning risk prediction model for asthma attacks in adults in primary care.

Primary care consultations provide an opportunity for patients and clinicians to assess asthma attac...

Digital image processing combined with machine learning: A novel approach for bee pollen classification.

The classification of bee pollen is crucial for ensuring product authenticity, quality control, and ...

Corrigendum to: Pollen analysis using multispectral imaging flow cytometry and deep learning.

Integrative analysis of signaling and metabolic pathways, immune infiltration patterns, and machine learning-based diagnostic model construction in major depressive disorder.

Major depressive disorder (MDD) is a multifactorial disorder involving genetic and environmental fac...

Applications of machine learning approaches for pediatric asthma exacerbation management: a systematic review.

BACKGROUND: Pediatric asthma is a common chronic respiratory disease worldwide, and its acute exacer...

Artificial Intelligence Models for Pediatric Lung Sound Analysis: Systematic Review and Meta-Analysis.

BACKGROUND: Pediatric respiratory diseases, including asthma and pneumonia, are major causes of morb...