Search alternatives:
stress optimization » step optimization (Expand Search), process optimization (Expand Search), task optimization (Expand Search)
while optimization » whale optimization (Expand Search), wolf optimization (Expand Search), phase optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data stress » data streams (Expand Search)
binary b » binary _ (Expand Search)
b while » b whole (Expand Search), a while (Expand Search)
stress optimization » step optimization (Expand Search), process optimization (Expand Search), task optimization (Expand Search)
while optimization » whale optimization (Expand Search), wolf optimization (Expand Search), phase optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data stress » data streams (Expand Search)
binary b » binary _ (Expand Search)
b while » b whole (Expand Search), a while (Expand Search)
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PathOlOgics_RBCs Python Scripts.zip
Published 2023“…</p><p><br></p><p dir="ltr">In the fifth measurement technique, the numbers of sharp <b>surface projections/protrusions</b> were calculated by initially applying Canny's edge detection algorithm to generate an edge map of the cell mask image. …”
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Table 1_Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis.docx
Published 2025“…Multiple machine learning algorithms, including Random Forest, XGBoost, Gradient Boosting, Logistic Regression, CatBoost, and MLP, were optimized and evaluated. …”
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Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
Published 2025“…</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…”