Search alternatives:
resource optimization » resource utilization (Expand Search), resource utilisation (Expand Search), resource limitations (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
data resource » data resources (Expand Search), data source (Expand Search), water resource (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
image model » damage model (Expand Search), primate model (Expand Search), climate model (Expand Search)
resource optimization » resource utilization (Expand Search), resource utilisation (Expand Search), resource limitations (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
data resource » data resources (Expand Search), data source (Expand Search), water resource (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
image model » damage model (Expand Search), primate model (Expand Search), climate model (Expand Search)
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Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf
Published 2024“…To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …”
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Natural language processing for automated quantification of bone metastases reported in free-text bone scintigraphy reports
Published 2020“…However, processing this rich resource of data for clinical and research purposes, depends on labor-intensive and potentially error-prone manual review. …”
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Thesis-RAMIS-Figs_Slides
Published 2024“…Importantly, this strategy locates samples adaptively on the transition between facies which improves the performance of conventional \emph{<i>MPS</i>} algorithms. In conclusion, this work shows that preferential sampling can contribute in \emph{<i>MPS</i>} even at very small sampling regimes and, as a corollary, demonstrates that prior models (obtained form a training image) can be used effectively not only to simulate non-sensed variables of the field, but to decide where to measure next.…”
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DataSheet_1_Exploring deep learning radiomics for classifying osteoporotic vertebral fractures in X-ray images.docx
Published 2024“…Logistic regression emerged as the optimal machine learning algorithm for both DLR models. …”
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Seed mix selection model
Published 2022“…The genetic algorithm then operated over 1000 iterations, applying crossover and mutation processes to optimize bee richness. …”
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Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
Published 2025“…</p><p dir="ltr">This curated dataset addresses several limitations of existing toxicological datasets by enhancing feature diversity, standardization, and data quality control. It is publicly available via the Supplementary Information section and aims to serve as a benchmark resource for researchers developing predictive nanotoxicology models.…”