Identification of Diagnostic Markers in Infantile Hemangiomas
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Oncology"
DOI: 10.1155/2022/9395876
Abstract: Background Infantile Hemangiomas (IHs) are common benign vascular tumors of infancy that may have serious consequences. The research on diagnostic markers for IHs is scarce. Methods The “limma” R package was applied to identify differentially… read more here.
Keywords: infantile hemangiomas; diagnostic genes; development; transcription factors ... See more keywords
Machine learning-based screening of the diagnostic genes and their relationship with immune-cell infiltration in patients with lung adenocarcinoma
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Thoracic Disease"
DOI: 10.21037/jtd-22-206
Abstract: Background Lung adenocarcinoma (LUAD) is the most common type of lung cancer, and has a dismal mortality rate of 80%, mainly due to diagnosis at an advanced stage. Biomarkers with high specificity and sensitivity for… read more here.
Keywords: lung adenocarcinoma; luad; machine; immune cell ... See more keywords
Identification of Potential Diagnostic Genes of HIV-Infected Immunological Non-Responders on Bioinformatics Analysis
Sign Up to like & getrecommendations! Published in 2023 at "Journal of Inflammation Research"
DOI: 10.2147/jir.s396055
Abstract: Purpose HIV-infected immunological non-responders (INRs) failed to achieve the normalization of CD4+ T cell counts despite their undetectable viral load. INRs have an increased risk of clinical progressions of Acquired Immunodeficiency Syndrome (AIDS) and non-AIDS… read more here.
Keywords: infected immunological; hiv infected; analysis; potential diagnostic ... See more keywords
Identification of the diagnostic genes and immune cell infiltration characteristics of gastric cancer using bioinformatics analysis and machine learning
Sign Up to like & getrecommendations! Published in 2023 at "Frontiers in Genetics"
DOI: 10.3389/fgene.2022.1067524
Abstract: Background: Finding reliable diagnostic markers for gastric cancer (GC) is important. This work uses machine learning (ML) to identify GC diagnostic genes and investigate their connection with immune cell infiltration. Methods: We downloaded eight GC-related… read more here.
Keywords: infiltration; machine learning; ontology; analysis ... See more keywords
Identification of new co-diagnostic genes for sepsis and metabolic syndrome using single-cell data analysis and machine learning algorithms
Sign Up to like & getrecommendations! Published in 2023 at "Frontiers in Genetics"
DOI: 10.3389/fgene.2023.1129476
Abstract: Sepsis, a serious inflammatory response that can be fatal, has a poorly understood pathophysiology. The Metabolic syndrome (MetS), however, is associated with many cardiometabolic risk factors, many of which are highly prevalent in adults. It… read more here.
Keywords: sepsis; cell; genes sepsis; metabolic syndrome ... See more keywords
Diagnostic model constructed by five EMT-related genes for renal fibrosis and reflecting the condition of immune-related cells
Sign Up to like & getrecommendations! Published in 2023 at "Frontiers in Immunology"
DOI: 10.3389/fimmu.2023.1161436
Abstract: Background Renal fibrosis is a physiological and pathological characteristic of chronic kidney disease (CKD) to end-stage renal disease. Since renal biopsy is the gold standard for evaluating renal fibrosis, there is an urgent need for… read more here.
Keywords: diagnostic model; renal fibrosis; model constructed; immune ... See more keywords