Allergy & Immunology

Allergy

Latest AI and machine learning research in allergy for healthcare professionals.

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Advancing sepsis diagnosis and immunotherapy machine learning-driven identification of stable molecular biomarkers and therapeutic targets.

Sepsis represents a significant global health challenge, necessitating early detection and effective...

Multimodal deep learning for predicting PD-L1 biomarker and clinical immunotherapy outcomes of esophageal cancer.

Although the immune checkpoint inhibitors (ICIs) have demonstrated remarkable anti-tumor efficacy in...

Elucidating the role of KCTD10 in coronary atherosclerosis: Harnessing bioinformatics and machine learning to advance understanding.

Atherosclerosis (AS) is increasingly recognized as a chronic inflammatory disease that significantly...

Transcriptome analysis reveals the potential role of neural factor EN1 for long-terms survival in estrogen receptor-independent breast cancer.

Breast cancer patients with estrogen receptor-negative (ERneg) status, encompassing triple negative ...

Development of a MVI associated HCC prognostic model through single cell transcriptomic analysis and 101 machine learning algorithms.

Hepatocellular carcinoma (HCC) is an exceedingly aggressive form of cancer that often carries a poor...

GRATCR: Epitope-Specific T Cell Receptor Sequence Generation With Data-Efficient Pre-Trained Models.

T cell receptors (TCRs) play a crucial role in numerous immunotherapies targeting tumor cells. Howev...

Machine learning analysis identified NNMT as a potential therapeutic target for hepatocellular carcinoma based on PCD-related genes.

Programmed cell death (PCD) plays a critical role in cancer biology, influencing tumor progression a...

Pretrained transformers applied to clinical studies improve predictions of treatment efficacy and associated biomarkers.

Cancer treatment has made significant advancements in recent decades, however many patients still ex...

Analytical and experimental solutions for Fourier transform infrared microspectroscopy measurements of microparticles: A case study on Quercus pollen.

BACKGROUND: FTIR microspectroscopy is a popular non-destructive technique for chemical analysis and ...

Modelling of pome fruit pollen performance using machine learning.

Agriculture, particularly fruit production, is considered a crucial industry with a significant econ...

Machine learning for early diagnosis of Kawasaki disease in acute febrile children: retrospective cross-sectional study in China.

Early diagnosis of Kawasaki disease (KD) allows timely treatment to be initiated, thereby preventing...

[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...

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...

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...

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