Relative predictive performance when training on gene-expression predictors alone vs. using clinical predictors alone or gene-expression predictors in combination with clinical pre... حسب Stephen R. Piccolo (8367780)

Summary of predictive performance per dataset when using gene-expression and clinical predictors and performing hyperparameter optimization. حسب Stephen R. Piccolo (8367780)

"…For classification algorithms that included multiple hyperparameter combinations (n = 47), we performed hyperparameter optimization using the respective training sets. …"

Algorithm 2: Maintain inhibitory densities coherence. حسب Dimitri Rodarie (10148838)

Image_1_Identification of a Novel Prognostic Signature for Gastric Cancer Based on Multiple Level Integration and Global Network Optimization.TIF حسب Lin Cui (163750)

"…To date, there have been no reports on integrated optimization analysis based on the GC global lncRNA-miRNA-mRNA network and the prognostic mechanism has not been studied. …"

Optimal image settings for object detection of Iba1 immunolabelled cells in DAB. حسب Danish M. Anwer (15383441)

DataSheet1_Optimal Sparsity Selection Based on an Information Criterion for Accurate Gene Regulatory Network Inference.PDF حسب Deniz Seçilmiş (13028616)

DataSheet1_Optimal Sparsity Selection Based on an Information Criterion for Accurate Gene Regulatory Network Inference.PDF حسب Deniz Seçilmiş (13028616)

Summary of predictive performance per dataset when using gene-expression predictors. حسب Stephen R. Piccolo (8367780)

Table1_Identification of biomarkers for hepatocellular carcinoma based on single cell sequencing and machine learning algorithms.DOCX حسب Weimin Li (131040)

"…Expression profiles of HCC cells and normal liver cells were first analyzed by maximum relevance minimum redundancy (mRMR) to get a top 50 signature gene feature. For further analysis, the incremental feature selection (IFS) method and leave-one-out cross validation (LOOCV) were conducted to build an optimal classification model and to extract 21 potentially essential biomarkers for HCC cells. …"

Optimal ovarian cancer BNs learned by CausNet and CausNet-partial. حسب Nand Sharma (21519845)

الموضوعات:

Algorithm 1: Cap inhibitory densities to number of neurons. حسب Dimitri Rodarie (10148838)

Summary of predictive performance per dataset when using gene-expression and clinical predictors. حسب Stephen R. Piccolo (8367780)

Comparison of ranks for classification algorithms across performance metrics. حسب Stephen R. Piccolo (8367780)

Table3_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX حسب Zhen Wang (72451)

"…Weighted gene coexpression network analysis (WGCNA) and two machine learning algorithms were employed to identify potential biomarkers for CRPC. …"

Table2_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX حسب Zhen Wang (72451)

"…Weighted gene coexpression network analysis (WGCNA) and two machine learning algorithms were employed to identify potential biomarkers for CRPC. …"

Table1_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX حسب Zhen Wang (72451)

"…Weighted gene coexpression network analysis (WGCNA) and two machine learning algorithms were employed to identify potential biomarkers for CRPC. …"

Summary of predictive performance per dataset when using gene-expression and clinical predictors and performing feature selection with hyperparameter optimization. حسب Stephen R. Piccolo (8367780)

Table 1_Leveraging a disulfidptosis-based signature to characterize heterogeneity and optimize treatment in multiple myeloma.docx حسب Bingxin Zhang (13011397)

Comparison of lower bounds in estimating kinetic parameters <i>k</i>_<i>i</i> obtained by HS-OED algorithm and GA,PSO-based OED methods. حسب Wei Zhang (405)

Initialization of variables in the APDCA algorithm. حسب Yangsong He (13909371)

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