Search alternatives:
model optimization » codon optimization (Expand Search), global optimization (Expand Search), wolf optimization (Expand Search)
dose optimization » based optimization (Expand Search), wolf optimization (Expand Search), fox optimization (Expand Search)
binary based » library based (Expand Search), binary mask (Expand Search), linac based (Expand Search)
binary risk » binary mask (Expand Search), dietary risk (Expand Search), primary risk (Expand Search)
based dose » based case (Expand Search), based dosing (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), wolf optimization (Expand Search)
dose optimization » based optimization (Expand Search), wolf optimization (Expand Search), fox optimization (Expand Search)
binary based » library based (Expand Search), binary mask (Expand Search), linac based (Expand Search)
binary risk » binary mask (Expand Search), dietary risk (Expand Search), primary risk (Expand Search)
based dose » based case (Expand Search), based dosing (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“…</p>Results and Discussion<p>Experimental evaluation across varied athlete cohorts demonstrates superior performance in risk stratification accuracy, diagnostic plausibility, and model transparency compared to traditional screening algorithms. …”
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Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat.
Published 2025“…Optimization with GridSearchCV corroborated this stagnation, identifying a simple linear model (C=0.05, gamma='scale') as the optimal configuration, indicating that the additional complexity of nonlinear kernels did not confer predictive gains. …”
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Table 1_Creating an interactive database for nasopharyngeal carcinoma management: applying machine learning to evaluate metastasis and survival.docx
Published 2024“…Five machine learning models were deployed for the binary classification task of DM, and their performance was evaluated using the area under the curve (AUC). …”
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Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
Published 2025“…</p><p dir="ltr">These biological metrics were used to define a binary toxicity label: entries were classified as toxic (1) or non-toxic (0) based on thresholds from standardized guidelines (e.g., ISO 10993-5:2009) and literature consensus. …”