AI Medical Compendium Journal:
Biology direct

Showing 1 to 10 of 25 articles

Identification of M2 macrophage-related genes associated with diffuse large B-cell lymphoma via bioinformatics and machine learning approaches.

Biology direct
M2 macrophages play a crucial role in the initiation and progression of various tumors, including diffuse large B-cell lymphoma (DLBCL). However, the characterization of M2 macrophage-related genes in DLBCL remains incomplete. In this study, we downl...

Integrating machine learning models with multi-omics analysis to decipher the prognostic significance of mitotic catastrophe heterogeneity in bladder cancer.

Biology direct
BACKGROUND: Mitotic catastrophe is well-known as a major pathway of endogenous tumor death, but the prognostic significance of its heterogeneity regarding bladder cancer (BLCA) remains unclear.

Large-scale bulk and single-cell RNA sequencing combined with machine learning reveals glioblastoma-associated neutrophil heterogeneity and establishes a VEGFA neutrophil prognostic model.

Biology direct
BACKGROUND: Neutrophils play a key role in the tumor microenvironment (TME); however, their functions in glioblastoma (GBM) are overlooked and insufficiently studied. A detailed analysis of GBM-associated neutrophil (GBMAN) subpopulations may offer n...

Exploring the role of oxidative stress in carotid atherosclerosis: insights from transcriptomic data and single-cell sequencing combined with machine learning.

Biology direct
BACKGROUND: Carotid atherosclerotic plaque is the primary cause of cardiovascular and cerebrovascular diseases. It is closely related to oxidative stress and immune inflammation. This bioinformatic study was conducted to identify key oxidative stress...

Uncovering glycolysis-driven molecular subtypes in diabetic nephropathy: a WGCNA and machine learning approach for diagnostic precision.

Biology direct
INTRODUCTION: Diabetic nephropathy (DN) is a common diabetes-related complication with unclear underlying pathological mechanisms. Although recent studies have linked glycolysis to various pathological states, its role in DN remains largely underexpl...

The role of endothelial cell-related gene COL1A1 in prostate cancer diagnosis and immunotherapy: insights from machine learning and single-cell analysis.

Biology direct
BACKGROUND: Endothelial cells are integral components of the tumor microenvironment and play a multifaceted role in tumor immunotherapy. Targeting endothelial cells and related signaling pathways can improve the effectiveness of immunotherapy by norm...

An exploration into the diagnostic capabilities of microRNAs for myocardial infarction using machine learning.

Biology direct
BACKGROUND: MicroRNAs (miRNAs) have shown potential as diagnostic biomarkers for myocardial infarction (MI) due to their early dysregulation and stability in circulation after MI. Moreover, they play a crucial role in regulating adaptive and maladapt...

Machine learning-driven estimation of mutational burden highlights DNAH5 as a prognostic marker in colorectal cancer.

Biology direct
BACKGROUND: Tumor Mutational Burden (TMB) have emerged as pivotal predictive biomarkers in determining prognosis and response to immunotherapy in colorectal cancer (CRC) patients. While Whole Exome Sequencing (WES) stands as the gold standard for TMB...

Machine learning model reveals the role of angiogenesis and EMT genes in glioma patient prognosis and immunotherapy.

Biology direct
Gliomas represent a highly aggressive class of tumors located in the brain. Despite the availability of multiple treatment modalities, the prognosis for patients diagnosed with glioma remains unfavorable. Therefore, further exploration of new biomark...

Identification of metastasis-related genes for predicting prostate cancer diagnosis, metastasis and immunotherapy drug candidates using machine learning approaches.

Biology direct
BACKGROUND: Prostate cancer (PCa) is the second leading cause of tumor-related mortality in men. Metastasis from advanced tumors is the primary cause of death among patients. Identifying novel and effective biomarkers is essential for understanding t...