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Enhancing Tire Condition Monitoring through Weightless Neural Networks Using MEMS-Based Vibration Signals
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Improving fluoroprobe sensor performance through machine learning
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Hybrid Model for 6G Network Traffic Prediction and Wireless Resource Optimization
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Data Mining Classification Techniques for Diabetes Prediction
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Acoustic-based models to assess herd-level calves' emotional state: A machine learning approach
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Eco-Driving Level Evaluation Model for Electric Buses Entering and Leaving Stops
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Hierarchical Classification of Variable Stars Using Deep Convolutional Neural Networks
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Neoantigen prioritization based on antigen processing and presentation
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UAV-Multispectral Based Maize Lodging Stress Assessment with Machine and Deep Learning Methods
Published 2024-12-01“…The results indicate that the Random Forest (RF) model outperforms the other four ML algorithms, achieving an overall accuracy (OA) of 89.29% and a Kappa coefficient of 0.8852. …”
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AI-powered IoT and UAV systems for real-time detection and prevention of illegal logging
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Development and Validation of DIANA (Diabetes Novel Subgroup Assessment tool): A web-based precision medicine tool to determine type 2 diabetes endotype membership and predict indi...
Published 2025-08-01“…Its performance was compared with an algorithm determined based on conditional pre-determined cut-offs and weights for each clinical feature [age at diagnosis, BMI, waist, HbA1c, Serum Triglycerides, HDL-Cholesterol, (C-peptide fasting, C-peptide stimulated) - optional. …”
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Rapid and accurate multi-phenotype imputation for millions of individuals
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The Efficiency of Complex Differential Treatment of the Patients with Systemic Lupus Erythematous Considering the Features of Bone Tissue Structure Remodeling
Published 2020-04-01“…The evaluation of the application forms of LQ proves this fact. A general score of the patients of research group has increased up to 37.93 % versus 3.19 % for the women of research group, the same has a complex objective evaluation of the results of treatment by the doctors and researchers: the patients out of research group experienced a positive result of treatment more often while the ones out of comparison group -satisfactory and negative. …”
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