Search alternatives:
derived optimization » driven optimization (Expand Search), required optimization (Expand Search), design optimization (Expand Search)
process optimization » robust optimization (Expand Search), model optimization (Expand Search), policy optimization (Expand Search)
image process » damage process (Expand Search), image processing (Expand Search), immune process (Expand Search)
data derived » data driven (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
derived optimization » driven optimization (Expand Search), required optimization (Expand Search), design optimization (Expand Search)
process optimization » robust optimization (Expand Search), model optimization (Expand Search), policy optimization (Expand Search)
image process » damage process (Expand Search), image processing (Expand Search), immune process (Expand Search)
data derived » data driven (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
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A* Path-Finding Algorithm to Determine Cell Connections
Published 2025“…</p><p dir="ltr">Astrocytes were dissociated from E18 mouse cortical tissue, and image data were processed using a Cellpose 2.0 model to mask nuclei. …”
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Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm
Published 2025“…This strategy </p><p dir="ltr">not only improves detection efficiency and accuracy but also supports early diagnosis and treatment planning, </p><p dir="ltr">leading to better patient outcomes. By leveraging the binary GWO algorithm to optimize the feature selection </p><p dir="ltr">process and CNNs for image classification, the proposed approach reduces computational costs while increasing </p><p dir="ltr">classification accuracy. …”
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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.…”