Search alternatives:
elimination algorithm » maximization algorithm (Expand Search), optimization algorithms (Expand Search), segmentation algorithm (Expand Search)
process optimization » model optimization (Expand Search)
data feature » data figure (Expand Search), each feature (Expand Search), a feature (Expand Search)
same process » damage process (Expand Search), simple process (Expand Search), phase process (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
binary same » binary image (Expand Search)
elimination algorithm » maximization algorithm (Expand Search), optimization algorithms (Expand Search), segmentation algorithm (Expand Search)
process optimization » model optimization (Expand Search)
data feature » data figure (Expand Search), each feature (Expand Search), a feature (Expand Search)
same process » damage process (Expand Search), simple process (Expand Search), phase process (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
binary same » binary image (Expand Search)
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Integrative Clinical and Bio-mechanical Features Predict In-Hospital Trauma Mortality
Published 2024Subjects: -
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Variable Selection and Estimation for Misclassified Binary Responses and Multivariate Error-Prone Predictors
Published 2023“…The simultaneous appearance of these complex features make data analysis become challenging. To address those concerns, we propose a valid inferential method to deal with measurement error and handle variable selection simultaneously. …”
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Image processing workflow.
Published 2020“…<p>Raw fluorescent microscope images (a) were processed with a binary segmentation algorithm, and clusters of bacterial cells were manually annotated. …”
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Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19.
Published 2021“…<p>(A). The MCDM algorithm-Stage 1. Preprocessing, this stage is the process of refining the collected raw data to eliminate noise, including correlation analysis and feature selection based on P values. …”
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Data_Sheet_3_sigFeature: Novel Significant Feature Selection Method for Classification of Gene Expression Data Using Support Vector Machine and t Statistic.docx
Published 2020“…Many feature selection algorithms have been developed including the support vector machine recursive feature elimination procedure (SVM-RFE) and its variants. …”
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Data_Sheet_2_sigFeature: Novel Significant Feature Selection Method for Classification of Gene Expression Data Using Support Vector Machine and t Statistic.docx
Published 2020“…Many feature selection algorithms have been developed including the support vector machine recursive feature elimination procedure (SVM-RFE) and its variants. …”
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Data_Sheet_1_sigFeature: Novel Significant Feature Selection Method for Classification of Gene Expression Data Using Support Vector Machine and t Statistic.docx
Published 2020“…Many feature selection algorithms have been developed including the support vector machine recursive feature elimination procedure (SVM-RFE) and its variants. …”
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Natural language processing for automated quantification of bone metastases reported in free-text bone scintigraphy reports
Published 2020“…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.…”
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Table_1_bSRWPSO-FKNN: A boosted PSO with fuzzy K-nearest neighbor classifier for predicting atopic dermatitis disease.docx
Published 2023“…In bSRWPSO-FKNN, the core of which is to optimize the classification performance of FKNN through binary SRWPSO.…”
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PathOlOgics_RBCs Python Scripts.zip
Published 2023“…This process generated a ground-truth binary semantic segmentation mask and determined the bounding box coordinates (XYWH) for each cell. …”
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