Allergy & Immunology

An assessment of machine learning methods to quantify blood lactate from neutrophils phagocytic activity.

Phagocytosis is a critical component of innate immunity that helps the body defend itself against in...

Integrated multiomics analysis and machine learning refine neutrophil extracellular trap-related molecular subtypes and prognostic models for acute myeloid leukemia.

BACKGROUND: Neutrophil extracellular traps (NETs) play pivotal roles in various pathological process...

[MP-MRI in the evaluation of non-operative treatment response, for residual and recurrent tumor detection in head and neck cancer].

As non-surgical therapies gain acceptance in head and neck tumors, the importance of imaging has inc...

From text to insight: A natural language processing-based analysis of burst and research trends in HER2-low breast cancer patients.

With the intensification of population aging, the proportion of elderly breast cancer patients is co...

Disease diagnostics using machine learning of B cell and T cell receptor sequences.

Clinical diagnosis typically incorporates physical examination, patient history, various laboratory ...

Radiomics and Deep Learning Prediction of Immunotherapy-Induced Pneumonitis From Computed Tomography.

PURPOSE: Primary barriers to application of immune checkpoint inhibitor (ICI) therapy for cancer inc...

G2M-checkpoint related immune barrier structure and signature for prognosis and immunotherapy response in hepatocellular carcinoma: insights from spatial transcriptome and machine learning.

BACKGROUND: Hepatocellular carcinoma (HCC) treatment remains challenging, particularly for immune ch...

Integration of 101 machine learning algorithm combinations to unveil m6A/m1A/m5C/m7G-associated prognostic signature in colorectal cancer.

Colorectal cancer (CRC) is the most common malignancy in the digestive system, with a lower 5-year o...

Multi-omics and single-cell analysis reveals machine learning-based pyrimidine metabolism-related signature in the prognosis of patients with lung adenocarcinoma.

Pyrimidine metabolism is a hallmark of tumor metabolic reprogramming, while its significance in the...

TimePAD─Unveiling Temporal Sequence ELISA Signal by Deep Learning for Rapid Readout and Improved Accuracy in a Microfluidic Paper-Based Analytical Platform.

The integration of paper-based microfluidics with deep learning represents a pivotal trend in enhanc...

Development and validation of MRI-derived deep learning score for non-invasive prediction of PD-L1 expression and prognostic stratification in head and neck squamous cell carcinoma.

BACKGROUND: Immunotherapy has revolutionized the treatment landscape for head and neck squamous cell...

CT-Based Deep Learning Predicts Prognosis in Esophageal Squamous Cell Cancer Patients Receiving Immunotherapy Combined with Chemotherapy.

RATIONALE AND OBJECTIVES: Immunotherapy combined with chemotherapy has improved outcomes for some es...

Artificial intelligence support improves diagnosis accuracy in anterior segment eye diseases.

CorneAI, a deep learning model designed for diagnosing cataracts and corneal diseases, was assessed ...

A privacy-preserved horizontal federated learning for malignant glioma tumour detection using distributed data-silos.

Malignant glioma is the uncontrollable growth of cells in the spinal cord and brain that look simila...

Web server-based deep learning-driven predictive models for respiratory toxicity of environmental chemicals: Mechanistic insights and interpretability.

Respiratory toxicity of chemicals is a common clinical and environmental health concern. Currently, ...

Using Facial Skin Artificial Intelligence (AI) to Capture Atopic Dermatitis Patients' Response to Therapy: A Single-Center Prospective Study.

Conditional similarity triplets enable covariate-informed representations of single-cell data.

BACKGROUND: Single-cell technologies enable comprehensive profiling of diverse immune cell-types thr...

Unlocking precision medicine: clinical applications of integrating health records, genetics, and immunology through artificial intelligence.

Artificial intelligence (AI) has emerged as a transformative force in precision medicine, revolution...

Utilizing bioinformatics and machine learning to identify CXCR4 gene-related therapeutic targets in diabetic foot ulcers.

BACKGROUND: Diabetic foot ulcers (DFUs) are a serious complication of diabetes mellitus that manifes...

Assessing the diagnostic accuracy of machine learning algorithms for identification of asthma in United States adults based on NHANES dataset.

Asthma diagnosis poses challenges due to underreporting of symptoms, misdiagnoses, and limitations i...

Multiple machine learning-based integrations of multi-omics data to identify molecular subtypes and construct a prognostic model for HNSCC.

BACKGROUND: Immunotherapy has introduced new breakthroughs in improving the survival of head and nec...