AIMC Topic: Boosting Machine Learning Algorithms

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Mitochondrial mt12361A>G increased risk of metabolic dysfunction-associated steatotic liver disease among non-diabetes.

World journal of gastroenterology Mar 14, 2025
BACKGROUND: Insulin resistance, lipotoxicity, and mitochondrial dysfunction contribute to the pathogenesis of metabolic dysfunction-associated steatotic liver disease (MASLD). Mitochondrial dysfunction impairs oxidative phosphorylation and increases ...
Polymorphism, Single Nucleotide Logistic Models Cohort Studies DNA, Mitochondrial Diabetes Complications Non-alcoholic Fatty Liver Disease Random Forest Male Case-Control Studies Middle Aged Humans Adult Boosting Machine Learning Algorithms
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A Tutorial and Use Case Example of the eXtreme Gradient Boosting (XGBoost) Artificial Intelligence Algorithm for Drug Development Applications.

Clinical and translational science Mar 1, 2025
Approaches to artificial intelligence and machine learning (AI/ML) continue to advance in the field of drug development. A sound understanding of the underlying concepts and guiding principles of AI/ML implementation is a prerequisite to identifying ...
Boosting Machine Learning Algorithms Algorithms Machine Learning Clinical Trials as Topic Drug Development Humans Artificial Intelligence
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Exploring Ensemble Learning Techniques for Infant Mortality Prediction: A Technical Analysis of XGBoost Stacking AdaBoost and Bagging Models.

Birth defects research Feb 1, 2025
BACKGROUND: Infant mortality remains a critical public health issue, reflecting the overall health and well-being of a population. Accurate prediction of infant mortality is crucial, as it enables healthcare providers to identify at-risk populations ...
Boosting Machine Learning Algorithms Humans Ensemble Learning Female India Machine Learning Infant, Newborn Infant Mortality Infant
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Forecasting monthly runoff in a glacierized catchment: A comparison of extreme gradient boosting (XGBoost) and deep learning models.

PloS one Jan 1, 2025
Accurate monthly runoff forecasting is vital for water management, flood control, hydropower, and irrigation. In glacierized catchments affected by climate change, runoff is influenced by complex hydrological processes, making precise forecasting eve...
Forecasting Deep Learning Climate Change Boosting Machine Learning Algorithms Models, Theoretical Switzerland
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Residual XGBoost regression-Based individual moving range control chart for Gross Domestic Product growth monitoring.

PloS one Jan 1, 2025
Accurate and reliable Gross Domestic Product (GDP) forecasting is indispensable for informed economic policymaking and risk management. Autocorrelation, a prevalent characteristic of macroeconomic time series, poses significant challenges to traditio...
Boosting Machine Learning Algorithms Forecasting Gross Domestic Product Regression Analysis Humans Algorithms Machine Learning
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The Diagnosis of Cardiovascular Disease Using Simple Blood Biomarkers Through AI and Big Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Cardiovascular disease (CVD) is the leading cause of global mortality, diagnosed primarily through costly imaging modalities which are often overused in asymptomatic patients. Our project aims to develop an AI-based solution for CVD risk stratificati...
Boosting Machine Learning Algorithms Humans Biomarkers UK Biobank Random Forest Middle Aged Risk Assessment Male Big Data Heart Disease Risk Factors Female
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