Search alternatives:
resource optimization » resource utilization (Expand Search), resource utilisation (Expand Search), resource limitations (Expand Search)
codon optimization » wolf optimization (Expand Search)
from resource » food resource (Expand Search), low resource (Expand Search), from research (Expand Search)
binary from » diary from (Expand Search), library from (Expand Search)
binary mask » binary image (Expand Search)
resource optimization » resource utilization (Expand Search), resource utilisation (Expand Search), resource limitations (Expand Search)
codon optimization » wolf optimization (Expand Search)
from resource » food resource (Expand Search), low resource (Expand Search), from research (Expand Search)
binary from » diary from (Expand Search), library from (Expand Search)
binary mask » binary image (Expand Search)
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Identification and quantitation of clinically relevant microbes in patient samples: Comparison of three k-mer based classifiers for speed, accuracy, and sensitivity
Published 2019“…We tested the accuracy, sensitivity, and resource requirements of three top metagenomic taxonomic classifiers that use fast k-mer based algorithms: Centrifuge, CLARK, and KrakenUniq. …”
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Natural language processing for automated quantification of bone metastases reported in free-text bone scintigraphy reports
Published 2020“…<p> The widespread use of electronic patient-generated health data has led to unprecedented opportunities for automated extraction of clinical features from free-text medical notes. 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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Seed mix selection model
Published 2022“…</p> <p> </p> <p>We applied the seed mix selection model using a binary genetic algorithm to select seed mixes (R package ‘GA’; Scrucca 2013; Scrucca 2017). …”
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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. …”