Search alternatives:
across optimization » cost optimization (Expand Search), stress optimization (Expand Search), process optimization (Expand Search)
dose optimization » based optimization (Expand Search), model optimization (Expand Search), wolf optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data dose » data due (Expand Search), data de (Expand Search)
across optimization » cost optimization (Expand Search), stress optimization (Expand Search), process optimization (Expand Search)
dose optimization » based optimization (Expand Search), model optimization (Expand Search), wolf optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data dose » data due (Expand Search), data de (Expand Search)
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Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
Published 2025“…Experimental Conditions:</b></p><p dir="ltr">To capture contextual variation in assay conditions, the dataset includes:</p><p dir="ltr">Exposure dose (µg/mL): Spanning 0–1000 µg/mL across studies.…”
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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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Table 1_Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis.docx
Published 2025“…Demographic, clinical, and heavy metal biomarker data (e.g., blood lead and cadmium levels) were analyzed as features, with hearing loss status—defined as a pure-tone average threshold exceeding 25 dB HL across 500, 1,000, 2000, and 4,000 Hz in the better ear—serving as the binary outcome. …”