The scheme of CARS-Logistic algorithm. by Maryam Sadiq (7046903)

Table 1_A comparative analysis of binary and multi-class classification machine learning algorithms to detect current frailty status using the English longitudinal study of ageing... by Charmayne Mary Lee Hughes (12959972)

“…</p>Conclusion<p>Machine learning algorithms show promise for the detection of current frailty status, particularly in binary classification. …”

Pseudocode of NSGAII [23]. by Seyed Mahdi Hosseiniyan Khatibi (16791475)

“…Next, to apply feature selection, a t-test and binary Non-Dominated Sorting Genetic Algorithm II (NSGAII) were chosen to be employed. …”

Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods by Jiacong Du (12035845)

“…Applying a variable selection algorithm on each imputed dataset will likely lead to different sets of selected predictors. …”

Effectiveness of image augmentation operations. by Hailang Li (12557543)

Seed mix selection model by Bethanne Bruninga-Socolar (10923639)

“…</p> <p>  </p> <p>We applied the seed mix selection model using a binary genetic algorithm to select seed mixes (R package ‘GA’; Scrucca 2013; Scrucca 2017). …”

EvoImp’s GA structure example. by Antonio Fernando Lavareda Jacob Junior (17816730)

High-order radiomics features based on T2 FLAIR MRI predict multiple glioma immunohistochemical features: A more precise and personalized gliomas management by Jing Li (10611)

“…Feature reduction was performed by ANOVA+ Mann-Whiney, spearman correlation analysis, least absolute shrinkage and selection operator (LASSO) and Gradient descent algorithm (GBDT). …”

An overview of the tech-flowchart of entire study. by Jing Li (10611)

GSE96058 information. by Sepideh Zununi Vahed (9861298)

“…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). …”

The performance of classifiers. by Sepideh Zununi Vahed (9861298)

“…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). …”

Min-Cut/Max-Flow Problem Instances for Benchmarking by Patrick Møller Jensen (7232042)

“…<div><div>Min-Cut/Max-Flow Problem Instances for Benchmarking </div><div><p>This is a collection of min-cut/max-flow problem instances that can be used for benchmarking min-cut/max-flow algorithms. The collection is released in companionship with the paper:</p> </div><div><ul><li>Jensen et al., “Review of Serial and Parallel Min-Cut/Max-Flow Algorithms for Computer Vision”.…”

Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield... by Uttam Khatri (12689072)

“…Finally, we implemented and compared the different feature selection algorithms to integrate the structural features, brain networks, and voxel features to optimize the diagnostic identifications of AD using support vector machine (SVM) classifiers. …”

Comprehensive view of <i>Trackoscope</i>: Design, interface, and tracking mechanics. by Priya Soneji (19105487)

Table_1_Angiotensin System Autoantibodies Correlate With Routine Prognostic Indicators for COVID-19 Severity.docx by Carmen M. Labandeira (12217994)

“…In 50 patients with a complete set of routine biochemical parameters, clinical data and disease outcome information, a Random Forest algorithm was used to select prognostic indicators, and the Spearman coefficient was used to analyze correlations with AT1-AA, ACE2-AA.…”

PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

“…</p><p dir="ltr">In terms of classification, a second algorithm was developed and employed to preliminary sort or group the individual cells (after excluding the overlapping cells manually) into different categories using five geometric measurements applied to the extracted contour from each binary image mask (see PathOlOgics_script_2; preliminary shape measurements). …”

Supplementary Material for: An Association Rule Analysis of Combined Acupoints for the Treatment of Patients with Dry Eye Disease by Lin Y.-H. (9860462)

“…<b><i>Methods:</i></b> We summarized 32 acupoints as binary data from the 12 eligible RCTs and analyzed them based on the Apriori algorithm. …”

DataSheet_1_Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.docx by Yuhong Huang (115702)

“…We then built 120 diagnostic models using distinct classification algorithms and feature sets divided by MRI sequences and selection strategies to predict molecular subtype and AR expression of breast cancer in the testing dataset of leave-one-out cross-validation (LOOCV). …”

Data_Sheet_4_Machine-Learning vs. Expert-Opinion Driven Logistic Regression Modelling for Predicting 30-Day Unplanned Rehospitalisation in Preterm Babies: A Prospective, Population... by Robert A. Reed (802828)

“…</p><p>Objective: To compare two machine-learning methods (least absolute shrinkage and selection operator (LASSO) and random forest) to expert-opinion driven logistic regression modelling for predicting unplanned rehospitalisation within 30 days in a large French cohort of preterm babies.…”

Table_2_Machine-Learning vs. Expert-Opinion Driven Logistic Regression Modelling for Predicting 30-Day Unplanned Rehospitalisation in Preterm Babies: A Prospective, Population-Base... by Robert A. Reed (802828)

“…</p><p>Objective: To compare two machine-learning methods (least absolute shrinkage and selection operator (LASSO) and random forest) to expert-opinion driven logistic regression modelling for predicting unplanned rehospitalisation within 30 days in a large French cohort of preterm babies.…”