Allergy

The value of artificial intelligence combined with multimodal data analysis in tumor immunotherapy and targeted therapy.

The advent of immunotherapy and targeted therapy has revolutionized oncology treatment in recent yea...

An odyssey of monoclonal gammopathies: focusing on precursors and the progression from MGUS and SMM to multiple Myeloma, with a brief overview of novel therapeutic strategies.

Monoclonal gammopathies span a continuum from monoclonal gammopathy of undetermined significance (MG...

Comparison of machine learning methods in forecasting and characterizing the birch and grass pollen season.

The primary approach to the treatment of seasonal allergic diseases involves minimizing exposure to ...

Nuclear medicine in predicting hepatocellular carcinoma response.

Immune checkpoint inhibitors and anti-angiogenic targeted therapies have improved outcomes in hepato...

The 487-gene expression profile test guides systemic therapy selection to improve outcomes for patients with atopic dermatitis: Results from a prospective trial.

BACKGROUND: Current atopic dermatitis (AD) therapy selection does not account for molecular drivers ...

Predictors of sensitivity to immune therapies in classic Hodgkin lymphoma.

Immune checkpoint blockade, particularly programmed cell death protein 1 inhibition, has redefined t...

Advancements and challenges in CAR-NK cell therapy for cancer treatment.

Chimeric antigen receptor natural killer (CAR-NK) cell therapy is an emerging cancer treatment offer...

Exploratory identification of COL1A1 as a potential gene linking endocrine-disrupting chemicals and lung adenocarcinoma: a bioinformatics and machine learning analysis.

BACKGROUND: Endocrine-disrupting chemicals (EDCs) are common environmental pollutants that affect hu...

Predicting neoadjuvant immunotherapy efficacy with machine learning models in non-small cell lung cancer: A systematic review and meta analysis.

BACKGROUND: The response of resectable non-small cell lung cancer (NSCLC) to neoadjuvant immunothera...

Molecular Stratification of Antiphospholipid Syndrome Through Integrative Analysis of the Whole-Blood RNA Transcriptome.

OBJECTIVE: Antiphospholipid syndrome (APS) is a thromboinflammatory disorder characterized by clinic...

artificial intelligence-enabled precision medicine for inflammatory skin diseases.

Recent advances in artificial intelligence (AI) and multimodal data collection are revolutionizing d...

Automating classification of treatment responses to combined targeted therapy and immunotherapy in HCC.

Tyrosine kinase inhibitor (TKI) combined with immunotherapy regimens are now widely used for treatin...

Improving machine-learning development in allergology: bridging the gap between open-access and cohort-based databases.

PURPOSE OF REVIEW: The advent of high-throughput data generation and artificial intelligence has tra...

The use of advanced machine learning to predict outcomes after atezolizumab plus bevacizumab for advanced hepatocellular carcinoma: a retrospective cohort study.

BACKGROUND: Combination immune checkpoint inhibitors are recommended as first-line therapy for advan...

Association of Circulating T Cell and Tumor Microenvironment Profiles with Immune Checkpoint Blockade Outcome in Sarcoma.

PURPOSE: Immune checkpoint blockade (ICB) benefits only a subset of sarcoma patients. Biomarkers of ...

Projected typical allergic diseases prevalence under changing environments based on multiple machine learning models.

Predictive modeling of molecular activity underlying physical cell-cell interactions.

Interactions between cells are central to tissue organization and function in health and disease. La...

Atopic Dermatitis in Denmark: Regional Variation.

Using national registers, this study investigates regional variations in the number of individuals w...

Integrative bioinformatics and experiments identify RIBC2 as a key regulator in the esophageal cancer.

Early detection of esophageal cancer (EC) remains a major challenge due to the limited understanding...

Proteomics-driven innovations in plant-based foods: Current advances, emerging technologies, and future perspectives.

Despite rapid market growth, plant-based foods such as meat analogs, plant-based milk, yogurt altern...

Development and validation of a machine learning stratified prediction model for early warning of anti-tuberculosis drug-induced liver injury risk based on real-world data: a retrospective cohort study.

OBJECTIVE: This study aimed to develop and validate stratified machine learning models for early pre...