بدائل البحث:
policy optimization » topology optimization (توسيع البحث), wolf optimization (توسيع البحث), process optimization (توسيع البحث)
a optimization » ai optimization (توسيع البحث), _ optimization (توسيع البحث), b optimization (توسيع البحث)
image policy » climate policy (توسيع البحث), time policy (توسيع البحث), leave policy (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
data a » data _ (توسيع البحث), data 1 (توسيع البحث), data b (توسيع البحث)
policy optimization » topology optimization (توسيع البحث), wolf optimization (توسيع البحث), process optimization (توسيع البحث)
a optimization » ai optimization (توسيع البحث), _ optimization (توسيع البحث), b optimization (توسيع البحث)
image policy » climate policy (توسيع البحث), time policy (توسيع البحث), leave policy (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
data a » data _ (توسيع البحث), data 1 (توسيع البحث), data b (توسيع البحث)
-
121
-
122
DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
منشور في 2024"…Cooking data were classified into binary and multiclass variables (CT4C and CT6C). …"
-
123
-
124
-
125
Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods
منشور في 2022"…Building on existing work, we (i) derive and implement efficient cyclic coordinate descent and majorization-minimization optimization algorithms for continuous and binary outcome data, (ii) incorporate adaptive shrinkage penalties, (iii) compare these methods through simulation, and (iv) develop an R package <i>miselect</i>. …"
-
126
-
127
An intelligent decision-making system for embryo transfer in reproductive technology: a machine learning-based approach
منشور في 2025"…The aim of this study is to build Machine learning (ML) decision-support models to predict the optimal range of embryo numbers to transfer, using data from infertile couples identified through literature reviews. …"
-
128
-
129
-
130
Table 1_Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis.docx
منشور في 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. …"
-
131
Image 1_A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology.png
منشور في 2025"…CardioSpectra formulates athlete profiles as multivariate probabilistic entities across latent diagnostic states, using sparsity-aware inference to generate interpretable risk predictions while optimizing a sensitivity-specificity trade-off tailored to clinical priorities. …"
-
132
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...
منشور في 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. …"
-
133
Flow diagram of the automatic animal detection and background reconstruction.
منشور في 2020"…All data used to create these plots are available from <a href="https://doi.org/10.25349/D9ZK50" target="_blank">https://doi.org/10.25349/D9ZK50</a>.…"
-
134
Models and Dataset
منشور في 2025"…<p dir="ltr"><b>P3DE (Parameter-less Population Pyramid with Deep Ensemble):</b><br>P3DE is a hybrid feature selection framework that combines the Parameter-less Population Pyramid (P3) metaheuristic optimization algorithm with a deep ensemble of autoencoders. …"
-
135
Flowchart of the entire pipeline.
منشور في 2024"…<p>First, the raw data is filtered and cleaned, and converted to a binary data format for faster reading (see Section Data retrieval and preprocessing). …"
-
136
Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
منشور في 2024"…Cooking data were classified into binary and multiclass variables (CT4C and CT6C). …"
-
137
Supplementary Material 8
منشور في 2025"…</li><li><b>Radial basis function kernel-support vector machine (RBF-SVM): </b>A more flexible version of SVM that uses a non-linear kernel to capture complex relationships in genomic data, improving classification accuracy.…"
-
138
Seed mix selection model
منشور في 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). …"
-
139
Table_1_Machine Learning Techniques in Blood Pressure Management During the Acute Phase of Ischemic Stroke.DOCX
منشور في 2022"…</p>Methods<p>This diagnostic accuracy study used retrospective data from MIMIC-III and eICU databases. Decision trees were constructed by a hierarchical binary recursive partitioning algorithm to predict the BP-lowering of 10–30% off the maximal value when antihypertensive treatment was given in patients with an extremely high BP (above 220/110 or 180/105 mmHg for patients receiving thrombolysis), according to the American Heart Association/American Stroke Association (AHA/ASA), the European Society of Cardiology, and the European Society of Hypertension (ESC/ESH) guidelines. …"
-
140
Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
منشور في 2025"…<p dir="ltr">This CSV file contains a comprehensively curated dataset comprising physicochemical descriptors and biological assay data for engineered metal oxide nanoparticles. …"