AI Medical Compendium Journal:
Frontiers in immunology

Showing 111 to 120 of 308 articles

Integrating omics data and machine learning techniques for precision detection of oral squamous cell carcinoma: evaluating single biomarkers.

Frontiers in immunology
INTRODUCTION: Early detection of oral squamous cell carcinoma (OSCC) is critical for improving clinical outcomes. Precision diagnostics integrating metabolomics and machine learning offer promising non-invasive solutions for identifying tumor-derived...

-targeted AI-driven vaccines: a paradigm shift in gastric cancer prevention.

Frontiers in immunology
, a globally prevalent pathogen Group I carcinogen, presents a formidable challenge in gastric cancer prevention due to its increasing antimicrobial resistance and strain diversity. This comprehensive review critically analyzes the limitations of con...

Multi-omics characterization and machine learning of lung adenocarcinoma molecular subtypes to guide precise chemotherapy and immunotherapy.

Frontiers in immunology
BACKGROUND: Lung adenocarcinoma (LUAD) is a heterogeneous tumor characterized by diverse genetic and molecular alterations. Developing a multi-omics-based classification system for LUAD is urgently needed to advance biological understanding.

Predicting patients with septic shock and sepsis through analyzing whole-blood expression of NK cell-related hub genes using an advanced machine learning framework.

Frontiers in immunology
BACKGROUND: Sepsis is a life-threatening condition that causes millions of deaths globally each year. The need for biomarkers to predict the progression of sepsis to septic shock remains critical, with rapid, reliable methods still lacking. Transcrip...

Research hotspots and trends for Duchenne muscular dystrophy: a machine learning bibliometric analysis from 2004 to 2023.

Frontiers in immunology
AIMS: The aim of this study was to conduct a bibliometric analysis of the relevant literature on Duchenne muscular dystrophy (DMD) to ascertain its current status, identify key areas of research and demonstrate the evolution of the field.

LRMAHpan: a novel tool for multi-allelic HLA presentation prediction using Resnet-based and LSTM-based neural networks.

Frontiers in immunology
INTRODUCTION: The identification of peptides eluted from HLA complexes by mass spectrometry (MS) can provide critical data for deep learning models of antigen presentation prediction and promote neoantigen vaccine design. A major challenge remains in...

A comprehensive neuroimaging review of the primary and metastatic brain tumors treated with immunotherapy: current status, and the application of advanced imaging approaches and artificial intelligence.

Frontiers in immunology
Cancer immunotherapy has emerged as a novel clinical therapeutic option for a variety of solid tumors over the past decades. The application of immunotherapy in primary and metastatic brain tumors continues to grow despite limitations due to the phys...

Evaluating the prognostic potential of telomerase signature in breast cancer through advanced machine learning model.

Frontiers in immunology
BACKGROUND: Breast cancer prognosis remains a significant challenge due to the disease's molecular heterogeneity and complexity. Accurate predictive models are critical for improving patient outcomes and tailoring personalized therapies.

Machine learning based anoikis signature predicts personalized treatment strategy of breast cancer.

Frontiers in immunology
BACKGROUND: Breast cancer remains a leading cause of mortality among women worldwide, emphasizing the urgent need for innovative prognostic tools to improve treatment strategies. Anoikis, a form of programmed cell death critical in preventing metasta...