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guided optimization » model optimization (Expand Search)
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121
DataSheet_2_Optimising Treatment Outcomes for Children and Adults Through Rapid Genome Sequencing of Sepsis Pathogens. A Study Protocol for a Prospective, Multi-Centre Trial (DIREC...
Published 2021“…</p>Methods<p>The DIRECT study is a pilot prospective, non-randomized multicentre trial of an integrated diagnostic and therapeutic algorithm combining rapid direct pathogen sequencing and software-guided, personalised antibiotic dosing in children and adults with sepsis on ICU.…”
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122
DataSheet_1_Optimising Treatment Outcomes for Children and Adults Through Rapid Genome Sequencing of Sepsis Pathogens. A Study Protocol for a Prospective, Multi-Centre Trial (DIREC...
Published 2021“…</p>Methods<p>The DIRECT study is a pilot prospective, non-randomized multicentre trial of an integrated diagnostic and therapeutic algorithm combining rapid direct pathogen sequencing and software-guided, personalised antibiotic dosing in children and adults with sepsis on ICU.…”
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124
Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield...
Published 2022“…Finally, we implemented and compared the different feature selection algorithms to integrate the structural features, brain networks, and voxel features to optimize the diagnostic identifications of AD using support vector machine (SVM) classifiers. …”
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125
Models and Dataset
Published 2025“…</p><p dir="ltr"><br></p><p dir="ltr"><b>RAO (Rao Optimization Algorithm):</b><br>RAO is a parameter-less optimization algorithm that updates solutions based on simple arithmetic operations involving the best and worst individuals in the population. …”
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126
Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
Published 2024“…Cooking data were classified into binary and multiclass variables (CT4C and CT6C). …”
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127
Supplementary Material 8
Published 2025“…</li><li><b>XGboost: </b>An optimized gradient boosting algorithm that efficiently handles large genomic datasets, commonly used for high-accuracy predictions in <i>E. coli</i> classification.…”
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128
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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129
Flow diagram of the automatic animal detection and background reconstruction.
Published 2020“…(E) The threshold value is calculated based on the histogram: it is the mean of the image subtracted by 4 (optimal value defined by trial and error). …”
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130
Supplementary file 2_Machine learning enables early risk stratification of hymenopteran stings: evidence from a tropical multicenter cohort.xlsx
Published 2025“…Questionnaires with >20% missing data were excluded. Mean substitution was applied for primary missing data imputation, with multiple imputation by chained equations (MICE) used for sensitivity analysis. …”
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131
Image 1_Machine learning enables early risk stratification of hymenopteran stings: evidence from a tropical multicenter cohort.png
Published 2025“…Questionnaires with >20% missing data were excluded. Mean substitution was applied for primary missing data imputation, with multiple imputation by chained equations (MICE) used for sensitivity analysis. …”
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132
Supplementary file 1_Machine learning enables early risk stratification of hymenopteran stings: evidence from a tropical multicenter cohort.docx
Published 2025“…Questionnaires with >20% missing data were excluded. Mean substitution was applied for primary missing data imputation, with multiple imputation by chained equations (MICE) used for sensitivity analysis. …”
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133
Image 2_Machine learning enables early risk stratification of hymenopteran stings: evidence from a tropical multicenter cohort.png
Published 2025“…Questionnaires with >20% missing data were excluded. Mean substitution was applied for primary missing data imputation, with multiple imputation by chained equations (MICE) used for sensitivity analysis. …”
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134
Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
Published 2025“…Details on the data sourcing process, prompt engineering strategies for large language model (LLM)-based extraction, and validation protocols are provided in the Supplementary Information section.…”