Example of the optimisation algorithm. حسب Laurens H. J. Krah (5823848)

The maximum accuracy (lowest error rate) with the least number of ANOVA-ranked genes achieved by different feature filtering methods and classification algorithms refined by SIRRFE... حسب Song Cui (553627)

Classification error rate (1-accuracy) <i>vs</i>. the top number of ranked genes used by models, constructed to distinguish each individual PAH patient group. حسب Song Cui (553627)

The feature selection process of the IG-GPSO. حسب Fangyuan Yang (2567629)

Classification error rate (1-accuracy) <i>vs</i>. the top number of ranked genes used by models, constructed to distinguish the HPAH <i>vs</i>. UMC patient groups. حسب Song Cui (553627)

The feature ranking grouping process of the IG-GPSO. حسب Fangyuan Yang (2567629)

Classification error rate (1-accuracy) <i>vs</i>. the top number of ranked genes used by models, constructed to distinguish the healthy control <i>vs</i>. the combination of HPAH a... حسب Song Cui (553627)

DataSheet1_SS-RNN: A Strengthened Skip Algorithm for Data Classification Based on Recurrent Neural Networks.pdf حسب Wenjie Cao (780652)

Image3_Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.TIFF حسب Jian-Kun Song (11711756)

"…Subsequently, a novel diagnostic model comprising PRGs for psoriasis was constructed using a random forest algorithm (ntree = 400). A receiver operating characteristic (ROC) analysis was used to evaluate the classification performance through both internal and external validation. …"

Image1_Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.TIFF حسب Jian-Kun Song (11711756)

"…Subsequently, a novel diagnostic model comprising PRGs for psoriasis was constructed using a random forest algorithm (ntree = 400). A receiver operating characteristic (ROC) analysis was used to evaluate the classification performance through both internal and external validation. …"

Image2_Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.TIFF حسب Jian-Kun Song (11711756)

"…Subsequently, a novel diagnostic model comprising PRGs for psoriasis was constructed using a random forest algorithm (ntree = 400). A receiver operating characteristic (ROC) analysis was used to evaluate the classification performance through both internal and external validation. …"

DataSheet2_Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.CSV حسب Jian-Kun Song (11711756)

"…Subsequently, a novel diagnostic model comprising PRGs for psoriasis was constructed using a random forest algorithm (ntree = 400). A receiver operating characteristic (ROC) analysis was used to evaluate the classification performance through both internal and external validation. …"

DataSheet3_Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.CSV حسب Jian-Kun Song (11711756)

"…Subsequently, a novel diagnostic model comprising PRGs for psoriasis was constructed using a random forest algorithm (ntree = 400). A receiver operating characteristic (ROC) analysis was used to evaluate the classification performance through both internal and external validation. …"

DataSheet1_Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.pdf حسب Jian-Kun Song (11711756)

"…Subsequently, a novel diagnostic model comprising PRGs for psoriasis was constructed using a random forest algorithm (ntree = 400). A receiver operating characteristic (ROC) analysis was used to evaluate the classification performance through both internal and external validation. …"

Machine learning-based microarray analyses indicate low-expression genes might collectively influence PAH disease حسب Song Cui (553627)

"…To summarize, integrated with state-of-the-art machine learning and novel feature refining algorithms, the most accurate models could provide near-perfect classification accuracies using very few (close to ten) low-expression genes.…"

Summary of positive datasets processing pipeline. حسب Efrat Cohen-Davidi (19485986)

"…<div><p>MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression post-transcriptionally. In animals, this regulation is achieved via base-pairing with partially complementary sequences on mainly 3’ UTR region of messenger RNAs (mRNAs). …"

Conventional unsupervised hierarchical clustering indicated poor patient group separation compared to machine learning-based models. حسب Song Cui (553627)

Expression values and standard errors of genes within each patient group under the optimal feature filtering method (ALOGA < 128) used for (blue bars) distinguishing each individua... حسب Song Cui (553627)

Survival curves of no chemo patients in the test set 1 (METABRIC) with respect to risk classifications for each signature. حسب Dimitrij Tschodu (12072160)

Survival curves of no chemo patients in the test set 2 (GSE96058) with respect to risk classifications for each signature. حسب Dimitrij Tschodu (12072160)