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model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
care process » care processes (Expand Search), cycle process (Expand Search), care access (Expand Search)
binary care » primary care (Expand Search), binary image (Expand Search), binary pairs (Expand Search)
binary 3d » binary _ (Expand Search), binary b (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
care process » care processes (Expand Search), cycle process (Expand Search), care access (Expand Search)
binary care » primary care (Expand Search), binary image (Expand Search), binary pairs (Expand Search)
binary 3d » binary _ (Expand Search), binary b (Expand Search)
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Psoas muscle CT radiomics-based machine learning models to predict response to infliximab in patients with Crohn’s disease
Published 2025“…<i>Z</i> score standardization and independent sample <i>t</i> test were applied to identify optimal predictive features, which were then utilized in seven ML algorithms for training and validation. …”
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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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Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
Published 2025“…</p><p dir="ltr">Encoding: Categorical variables such as surface coating and cell type were grouped into logical classes and label-encoded to enable model compatibility.</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.…”