Allergy

A Metabolism-Driven Prognostic Model and PSMD14-SP1-GYS1 Axis Reveal Therapeutic Vulnerabilities in Melanoma.

Melanoma is a highly aggressive cutaneous malignancy characterized by a strong propensity for metast...

Machine learning in allergy research: A bibliometric review.

The emergence of big data and analytic approaches initiated research efforts to characterise differe...

Harnessing biomarkers to guide immunotherapy in esophageal cancer: toward precision oncology.

Esophageal cancer (EC) is one of the most serious health issues around the world, ranking seventh am...

LYnet: Computational identification of tumor T cell antigens using convolutional and recurrent neural networks.

BACKGROUND: Immunotherapy represents a paradigm shift in oncology, offering advantages in efficacy a...

Selenium biofortification: integrating one health and sustainability.

Selenium (Se) biofortification in crops has emerged as a promising strategy to address global Se def...

A machine learning-driven transcriptomic study reveals the key role of Romo1 in reversing central sensitization through stellate ganglion block in migraine: An interventional study based on a recurrent migraine rat model.

OBJECTIVES/BACKGROUND: This study utilized a nitroglycerin (NTG)-induced chronic migraine rat model ...

A machine learning platform for genotype-specific cardiotoxicity risk prediction using patient-derived iPSC-CMs.

INTRODUCTION: Drug-induced Torsades de Pointes (TdP) has led to withdrawal of several drugs from the...

AI Prognostication in Nonsmall Cell Lung Cancer: A Systematic Review.

The systematic literature review was performed on the use of artificial intelligence (AI) algorithms...

Can a Rule-Based Expert System Diagnose Nasal Obstruction from Nasoendoscopy Videos?

Nasal obstruction has multiple causes requiring specialist endoscopy for diagnosis. A rule-based exp...

iALP: Identification of Allergenic Proteins Based on Large Language Model and Gate Linear Unit.

The rising incidence of allergic disorders has emerged as a pressing public health issue worldwide, ...

Integrative analysis of multi-omics data and gut microbiota composition reveals prognostic subtypes and predicts immunotherapy response in colorectal cancer using machine learning.

Colorectal cancer (CRC) exhibits substantial heterogeneity in molecular subtypes and clinical outcom...

Development and validation of a prognostic model for predicting survival and immunotherapy benefits in melanoma based on metabolism-relevant genes.

Skin cutaneous melanoma (SKCM) is a fatal form of skin cancer. Metabolism-related genes (MRGs) compr...

Single-cell spatial transcriptomics reveals immunotherapy-driven bone marrow niche remodeling in AML.

Given the graft-versus-leukemia effect observed with allogeneic hematopoietic stem cell transplantat...

Computation strategies and clinical applications in neoantigen discovery towards precision cancer immunotherapy.

Neoantigens, which are tumor-specific peptides generated by malignant cells, can be presented to T c...

Leveraging machine learning models to evaluate immune infiltration in the ovarian cancer microenvironment: a single-cell analysis approach.

BACKGROUND: The prognosis of ovarian cancer is closely related to the degree of immune cell infiltra...

Analysis of Single-Cell RNA-Seq Data to Investigate Tumor Cell Heterogeneity in Uroepithelial Bladder Cancer and Predict Immunotherapy Response.

BACKGROUND: Numerous studies have suggested a close association between cancer stem cells (CSCs) and...

Metabolic alterations driven by LDHA in CD8 + T cells promote immune evasion and therapy resistance in NSCLC.

Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related deaths worldwide. Despite ad...

Deep learning-based allergic rhinitis diagnosis using nasal endoscopy images.

Allergic rhinitis typically has edematous and pale turbinates or erythematous and inflamed turbinate...

Corrigendum to 'CT-Based Deep Learning Predicts Prognosis in Esophageal Squamous Cell Cancer Patients Receiving Immunotherapy Combined with Chemotherapy' [Acad Radiol 32/6 (2025) 3397-3409].

Multi-omics analysis identifies SNP-associated immune-related signatures by integrating Mendelian randomization and machine learning in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death globally, characterized by...

Identification and single-cell analysis of prognostic genes related to mitochondrial and neutrophil extracellular traps in bladder cancer.

The development of bladder cancer (BLCA) is associated with mitochondrial dysfunction and neutrophil...