The main workflow of the proposed algorithm. حسب Xin Li (51274)

For each classification algorithm, the classification accuracies for binary subject groups NC versus EMCI, NC versus LEMC, EMCI versus LEMC, EMCI versus AD, LMCI versus AD, AD vers... حسب Qian Zhang (49333)

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 under various classification tasks, including: the multiclass classification for distinguishing each individual PAH patient group (Control <i>vs</i>.... حسب Song Cui (553627)

"…<p>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 under various classification tasks, including: the multiclass classification for distinguishing each individual PAH patient group (Control <i>vs</i>. …"

Representation of the feature selection algorithm. حسب Betty Wutzl (6945248)

ROC curves comparing the ML performance with three datasets groups (the thin line represents each iteration’s ROC, and the thick line is the mean ROC). حسب Tarun Gangil (14266311)

<i>hi</i>PRS algorithm process flow. حسب Michela C. Massi (14599915)

Skeletonisation algorithm. حسب Jordan Hembrow (16908051)

Segmentation, trace denoising and spike extraction framework. حسب Changjia Cai (10647521)

Region-specific variable importance. حسب Katherine E. Overly (10789206)

"…Then, we developed ESDM models to analyze fish distribution using the highest-performing algorithms for each region. Model performance was evaluated for each ensemble model, with all depicting ‘excellent’ predictive capability (AUC > 0.8). …"

Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf حسب Cecilia Lindig-León (7889777)

"…In this way, for each binary problem, the CSP algorithm produces features to determine if the specific body part is engaged in the task or not. …"

<b>Multimodal MRI radiomics</b><b> based on </b><b>habitat subregions of the tumor microenvironment</b><b> for predicting risk stratification in glioblastoma</b> حسب Han Wang (21457334)

"…All the segmentation results were manually reviewed and corrected using ITK-SNAP to ensure accuracy. Following segmentation, quantitative imaging phenomic (QIP) features were derived from each tumor subregion with the Cancer Imaging Phenomics Toolkit (CaPTk) in accordance with the guidelines established by the Image Biomarker Standardisation Initiative (IBSI).…"

Statistics in Proteomics: A Meta-analysis of 100 Proteomics Papers Published in 2019 حسب David C. L. Handler (8791451)

"…These data were then transformed to binary inputs, analyzed via machine learning algorithms, and classified accordingly, with the aim of determining if clusters of data existed for specific journals or if certain statistical measures correlated with each other. …"

The association between cerebral small vessel disease and unfavorable hematoma morphology in primary intracerebral hemorrhage حسب Wenqi Jiang (1638793)

"…The unfavorable hematoma morphology included any hypodensity, any irregularity, black hole, blend sign, Barras shape score ≥3, Barras density score ≥3, immature hematoma and combined Barras total score (CBTS) ≥4. The combined hematoma morphology score (CHMS) was evaluated by allocating 1 point for the presence of each of the mentioned unfavorable hematoma morphology. …"

Natural language processing for automated quantification of bone metastases reported in free-text bone scintigraphy reports حسب Olivier Q. Groot (9370461)

"…The aim of this study was to develop a natural language processing (NLP) algorithm for binary classification (single metastasis versus two or more metastases) in bone scintigraphy reports of patients undergoing surgery for bone metastases.…"

PathOlOgics_RBCs Python Scripts.zip حسب 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). …"

Table_1_Pan-Genomic and Polymorphic Driven Prediction of Antibiotic Resistance in Elizabethkingia.xlsx حسب Bryan Naidenov (6915392)

"…Using core-SNPs and pan-genes in combination with six machine learning (ML) algorithms, binary classification of clindamycin and vancomycin resistance achieved f1 scores of 0.94 and 0.84, respectively. …"

Image_1_Pan-Genomic and Polymorphic Driven Prediction of Antibiotic Resistance in Elizabethkingia.tif حسب Bryan Naidenov (6915392)

"…Using core-SNPs and pan-genes in combination with six machine learning (ML) algorithms, binary classification of clindamycin and vancomycin resistance achieved f1 scores of 0.94 and 0.84, respectively. …"

Image_2_Pan-Genomic and Polymorphic Driven Prediction of Antibiotic Resistance in Elizabethkingia.tif حسب Bryan Naidenov (6915392)

"…Using core-SNPs and pan-genes in combination with six machine learning (ML) algorithms, binary classification of clindamycin and vancomycin resistance achieved f1 scores of 0.94 and 0.84, respectively. …"

Data_Sheet_1_Improving Crowdsourcing-Based Image Classification Through Expanded Input Elicitation and Machine Learning.PDF حسب Romena Yasmin (12970919)

"…Experiment results suggest that more accurate results can be achieved with smaller training datasets when both the crowdsourced binary classification labels and the average of the self-reported confidence values in these labels are used as features for the ML classifiers. …"

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

"…Objective<p>To investigate whether radiomics features extracted from multi-parametric MRI combining machine learning approach can predict molecular subtype and androgen receptor (AR) expression of breast cancer in a non-invasive way.…"