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driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
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binary data » primary data (Expand Search), dietary data (Expand Search)
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driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
stress optimization » step optimization (Expand Search), process optimization (Expand Search), task optimization (Expand Search)
binary state » binary image (Expand Search)
state driven » data driven (Expand Search), wave driven (Expand Search), atp driven (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data stress » data streams (Expand Search)
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Image 1_A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology.png
Published 2025“…CardioSpectra formulates athlete profiles as multivariate probabilistic entities across latent diagnostic states, using sparsity-aware inference to generate interpretable risk predictions while optimizing a sensitivity-specificity trade-off tailored to clinical priorities. …”
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PathOlOgics_RBCs Python Scripts.zip
Published 2023“…</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). …”
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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.…”