Allergy

Artificial Intelligence for Head and Neck Squamous Cell Carcinoma: From Diagnosis to Treatment.

Head and neck squamous cell carcinoma (HNSCC) remains a globally prevalent malignancy with high morbidity and mortality. Despite therapeutic advances, patient outcomes are hindered by tumor heterogeneity, treatment-related toxicity, and the limitations of traditional prognostic tools. Artificial intelligence (AI) offers the opportunity to improve personalized HNSCC management by integrating comple...

Systematic Review: Use of Artificial Intelligence and Unmet Needs in Eosinophilic Oesophagitis.

BACKGROUND: Artificial intelligence (AI) has been applied extensively to eosinophilic oesophagitis (EoE), but its clinical impact and comprehensiveness remain unclear.

Machine learning-based integration develops relapse related signature for predicting prognosis and indicating immune microenvironment infiltration in breast cancer.

Breast cancer is the most common type of cancer in women, and while current treatments can cure the majority of early-stage primary BC cases, recurren...

Machine learning and multi-omics analysis reveal key regulators of proneural-mesenchymal transition in glioblastoma.

Glioblastoma (GBM) is classified into subtypes according to the molecular expression profile; the proneural subtype has a relatively good prognosis, a...

Clinical Management of Wasp Stings Using Large Language Models: Cross-Sectional Evaluation Study.

BACKGROUND: Wasp stings are a significant public health concern in many parts of the world, particularly in tropical and subtropical regions. The veno...

AI-Driven Biomarker Discovery and Personalized Allergy Treatment: Utilizing Machine Learning and NGS.

PURPOSE OF REVIEW: This review explores the transformative potential of artificial intelligence (AI) and next-generation sequencing (NGS) in allergy d...

Artificial Intelligence in Patch Testing: Comprehensive Review of Current Applications and Future Prospects in Dermatology.

BACKGROUND: The integration of artificial intelligence (AI) into patch testing for allergic contact dermatitis (ACD) holds the potential to standardiz...

Tumor-specific draining lymph node CD8 T cells orchestrate an anti-tumor response to neoadjuvant PD-1 immune checkpoint blockade.

Elucidating the anti-tumor role of tumor-draining lymph nodes (tdLNs) in patients could offer critical mechanistic insight and shift therapeutic strat...

From Molecular Precision to Clinical Practice: A Comprehensive Review of Bispecific and Trispecific Antibodies in Hematologic Malignancies.

Multispecific antibodies have redefined the immunotherapeutic landscape in hematologic malignancies. Bispecific antibodies (BsAbs), which redirect cyt...

Aerosol Measurements and Decadal Changes: The Role of Climatic Changes and How It Reflects in Respiratory Allergies and Asthma.

The causative agents of respiratory allergies are bioaerosols, such as house dust mite feces, pollen grains, and fungal spores. Climate change and urb...

NeoPred: dual-phase CT AI forecasts pathologic response to neoadjuvant chemo-immunotherapy in NSCLC.

BACKGROUND: Accurate preoperative prediction of major pathological response or pathological complete response after neoadjuvant chemo-immunotherapy re...

Development and interpretation of a pathomics-based model for the prediction of immune therapy response in colorectal cancer.

Colorectal cancer (CRC) is the third most common malignancy and the second leading cause of cancer-related deaths worldwide, with a 5-year survival ra...

Mechanical Modulation, Physiological Roles, and Imaging Innovations of Intercellular Calcium Waves in Living Systems.

Long-range intercellular communication is essential for multicellular biological systems to regulate multiscale cell-cell interactions and maintain li...

Revolutionizing breast cancer immunotherapy by integrating AI and nanotechnology approaches: review of current applications and future directions.

Breast cancer (BC) is still the most diagnosed cancer for females with an increased focus on immunotherapy as a promising precise treatment. Selecting...

Uncovering Key Features for Predicting Comorbid Chronic Eosinophilic Pneumonia in Chronic Rhinosinusitis via Machine Learning.

BACKGROUND: Chronic eosinophilic pneumonia (CEP) can occur concurrently with chronic rhinosinusitis (CRS). However, crucial features of comorbid CEP i...

Integrated Single-Cell and Bulk RNA Sequencing Analysis Identifies a Regulated Cell Death-Related Gene Signature for Predicting Prognosis and Therapeutic Responses in Cutaneous Melanoma.

Regulated cell death (RCD) is crucial for the advancement of cancers, and providing opportunities as prognostic indicators and immunotherapy markers f...

Unraveling the TEC-associated landscape in hepatocellular carcinoma: a comprehensive study based on multi-omics analyses.

The tumor microenvironment (TME) plays a pivotal role in tumor progression, immune evasion, and therapeutic responses. Among its key components, endot...

Development of an immune scoring system based on exosome-related gene expression for prognosis and treatment response prediction in breast cancer.

Breast cancer (BC) is a heterogeneous disease with diverse subtypes that influence prognosis and treatment outcomes. While advances have been made in ...

A review of enhanced biosignature immunotherapy tools for predicting lung cancer immune phenotypes using deep learning.

Cancer has increasingly been recognized as a genetic disease, influenced by lifestyle changes, dietary patterns, and environmental pollutants. Lung ca...

Cell death-related signature genes: risk-predictive biomarkers and potential therapeutic targets in severe sepsis.

Sepsis is a systemic inflammatory response syndrome that predisposes to severe lung infections (SeALAR) such as sepsis-associated acute lung injury (S...