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Assessing individual genetic susceptibility to metabolic syndrome: interpretable machine learning method
Published 2025-12-01“…Furthermore, the model combining conventional risk factors and GRS exhibited excellent discriminative performance (AUC = 0.962) and outstanding robustness (mean ROC-AUC = 0.959).Conclusion This study established a reliable XGBoost-based GRS model and a GRS prediction platform (https://metabolicsyndromeapps.shinyapps.io/geneticriskscore/) to assess individual genetic susceptibility to MetS. …”
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A Novel Forecasting Framework for Carbon Emission Trading Price Based on Nonlinear Integration
Published 2025-05-01Get full text
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Study on the effect of water on the shear behavior and microstructure of red mudstone
Published 2024-12-01Get full text
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Comparative Evaluation of Ensemble Machine Learning Models for Methane Production from Anaerobic Digestion
Published 2025-03-01Get full text
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Predictive genetic circuit design for phenotype reprogramming in plants
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An empirical study of the naïve REINFORCE algorithm for predictive maintenance
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A TARGET database-driven nomogram for pediatric osteosarcoma prognosis
Published 2025-08-01Get full text
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DI4SHE: Deep Learning via Incremental Capacity Analysis for Sodium Battery State-of-Health Estimation
Published 2025-05-01Get full text
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