Unveiling the ageing-related genes in diagnosing osteoarthritis with metabolic syndrome by integrated bioinformatics analysis and machine learning by Jian Huang (7250)

“…The limma package was used to identify differentially expressed genes (DEGs), and weighted gene coexpression network analysis (WGCNA) screened gene modules, and machine learning algorithms, such as random forest (RF), support vector machine (SVM), generalised linear model (GLM), and extreme gradient boosting (XGB), were employed. …”

Image 3_Multi-omics reveals efferocytosis-related hub genes as biomarkers for ustekinumab response in colitis.pdf by Jun-meng Wang (9959245)

“…Machine learning algorithms screened hub genes, followed by molecular docking to assess interactions with UST. …”

Image 3_High-parameter immunophenotyping reveals distinct immune cell profiles in pruritic dogs and cats.png by Erin McDonald (3535409)

“…</p>Methods<p>This pilot study employs high parameter immunophenotyping panels (15 markers for dog, 12 for cat) and leverages unsupervised clustering to identify immune cell populations. Our analysis uses machine learning and statistical algorithms to perform unsupervised clustering, multiple visualizations, and statistical analysis of high parameter flow cytometry data. …”

Image 4_High-parameter immunophenotyping reveals distinct immune cell profiles in pruritic dogs and cats.png by Erin McDonald (3535409)

“…</p>Methods<p>This pilot study employs high parameter immunophenotyping panels (15 markers for dog, 12 for cat) and leverages unsupervised clustering to identify immune cell populations. Our analysis uses machine learning and statistical algorithms to perform unsupervised clustering, multiple visualizations, and statistical analysis of high parameter flow cytometry data. …”

Image 1_Multi-omics reveals efferocytosis-related hub genes as biomarkers for ustekinumab response in colitis.tif by Jun-meng Wang (9959245)

“…Machine learning algorithms screened hub genes, followed by molecular docking to assess interactions with UST. …”

Image 4_Multi-omics reveals efferocytosis-related hub genes as biomarkers for ustekinumab response in colitis.pdf by Jun-meng Wang (9959245)

“…Machine learning algorithms screened hub genes, followed by molecular docking to assess interactions with UST. …”

Image 1_High-parameter immunophenotyping reveals distinct immune cell profiles in pruritic dogs and cats.png by Erin McDonald (3535409)

“…</p>Methods<p>This pilot study employs high parameter immunophenotyping panels (15 markers for dog, 12 for cat) and leverages unsupervised clustering to identify immune cell populations. Our analysis uses machine learning and statistical algorithms to perform unsupervised clustering, multiple visualizations, and statistical analysis of high parameter flow cytometry data. …”

Table 2_Multi-omics reveals efferocytosis-related hub genes as biomarkers for ustekinumab response in colitis.csv by Jun-meng Wang (9959245)

“…Machine learning algorithms screened hub genes, followed by molecular docking to assess interactions with UST. …”

Image 5_Multi-omics reveals efferocytosis-related hub genes as biomarkers for ustekinumab response in colitis.tif by Jun-meng Wang (9959245)

“…Machine learning algorithms screened hub genes, followed by molecular docking to assess interactions with UST. …”

Image 5_High-parameter immunophenotyping reveals distinct immune cell profiles in pruritic dogs and cats.png by Erin McDonald (3535409)

“…</p>Methods<p>This pilot study employs high parameter immunophenotyping panels (15 markers for dog, 12 for cat) and leverages unsupervised clustering to identify immune cell populations. Our analysis uses machine learning and statistical algorithms to perform unsupervised clustering, multiple visualizations, and statistical analysis of high parameter flow cytometry data. …”

Image 6_Multi-omics reveals efferocytosis-related hub genes as biomarkers for ustekinumab response in colitis.pdf by Jun-meng Wang (9959245)

“…Machine learning algorithms screened hub genes, followed by molecular docking to assess interactions with UST. …”

Image 2_High-parameter immunophenotyping reveals distinct immune cell profiles in pruritic dogs and cats.png by Erin McDonald (3535409)

“…</p>Methods<p>This pilot study employs high parameter immunophenotyping panels (15 markers for dog, 12 for cat) and leverages unsupervised clustering to identify immune cell populations. Our analysis uses machine learning and statistical algorithms to perform unsupervised clustering, multiple visualizations, and statistical analysis of high parameter flow cytometry data. …”

Table 1_Multi-omics reveals efferocytosis-related hub genes as biomarkers for ustekinumab response in colitis.csv by Jun-meng Wang (9959245)

“…Machine learning algorithms screened hub genes, followed by molecular docking to assess interactions with UST. …”

Table 1_High-parameter immunophenotyping reveals distinct immune cell profiles in pruritic dogs and cats.docx by Erin McDonald (3535409)

“…</p>Methods<p>This pilot study employs high parameter immunophenotyping panels (15 markers for dog, 12 for cat) and leverages unsupervised clustering to identify immune cell populations. Our analysis uses machine learning and statistical algorithms to perform unsupervised clustering, multiple visualizations, and statistical analysis of high parameter flow cytometry data. …”

Image 2_Multi-omics reveals efferocytosis-related hub genes as biomarkers for ustekinumab response in colitis.pdf by Jun-meng Wang (9959245)

“…Machine learning algorithms screened hub genes, followed by molecular docking to assess interactions with UST. …”

Table 3_Machine learning-based diagnostic model of lymphatics-associated genes for new therapeutic target analysis in intervertebral disc degeneration.xlsx by Maoqiang Lin (17046318)

“…Subsequently, four machine learning algorithms (SVM-RFE, Random Forest, XGB, and GLM) were used to select the method to construct the diagnostic model. …”

Table 4_Machine learning-based diagnostic model of lymphatics-associated genes for new therapeutic target analysis in intervertebral disc degeneration.xlsx by Maoqiang Lin (17046318)

“…Subsequently, four machine learning algorithms (SVM-RFE, Random Forest, XGB, and GLM) were used to select the method to construct the diagnostic model. …”

Table 2_Machine learning-based diagnostic model of lymphatics-associated genes for new therapeutic target analysis in intervertebral disc degeneration.xlsx by Maoqiang Lin (17046318)

“…Subsequently, four machine learning algorithms (SVM-RFE, Random Forest, XGB, and GLM) were used to select the method to construct the diagnostic model. …”

Table 1_Machine learning-based diagnostic model of lymphatics-associated genes for new therapeutic target analysis in intervertebral disc degeneration.xlsx by Maoqiang Lin (17046318)

“…Subsequently, four machine learning algorithms (SVM-RFE, Random Forest, XGB, and GLM) were used to select the method to construct the diagnostic model. …”

Table 1_A machine learning-based predictive model for the occurrence of lower extremity deep vein thrombosis after laparoscopic surgery in abdominal surgery.xlsx by Su-Zhen Yang (21448877)

“…Eleven key features were identified through group comparisons and used for model development. Twenty machine learning algorithms were evaluated, and the top five algorithms were used to build the final model by stacking.…”