AIMC Topic: Boosting Machine Learning Algorithms

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Construction of VAE-GRU-XGBoost intrusion detection model for network security.

PloS one Jun 25, 2025
With the advent of the big data era, the threat of network security is becoming increasingly severe. In order to cope with complex network attacks and ensure network security, a network intrusion detection model is constructed relying on deep learnin...
Computer Communication Networks Deep Learning Models, Theoretical Computer Security Boosting Machine Learning Algorithms Humans Algorithms
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Demographic forecast modelling using SSA-XGBoost for smart population management based on multi-sources data.

PloS one Jun 25, 2025
Population prediction could provide effective data support for social and economic planning and decision-making, especially for the sub-national population forecasting accurately. In addition to realizing efficient smart population management, this r...
Demography Boosting Machine Learning Algorithms Cell Phone Humans Machine Learning Algorithms Forecasting Female Male Population Dynamics
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Predicting carbapenem-resistant Pseudomonas aeruginosa infection risk using XGBoost model and explainability.

Scientific reports Jun 5, 2025
The prevalence and spread of carbapenem-resistant Pseudomonas aeruginosa (CRPA) is a global public health problem. This study aims to identify the risk factors of CRPA infection and construct a machine learning model to provide a prediction tool for ...
Adult Drug Resistance, Bacterial Boosting Machine Learning Algorithms Male Humans Female Pseudomonas aeruginosa Middle Aged Risk Factors Machine Learning Carbapenems Aged ROC Curve Anti-Bacterial Agents Cross Infection Pseudomonas Infections
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Detection of Depressive Symptoms in College Students Using Multimodal Passive Sensing Data and Light Gradient Boosting Machine: Longitudinal Pilot Study.

JMIR formative research Jun 3, 2025
BACKGROUND: Depression is the top contributor to global disability. Early detection of depression and depressive symptoms enables timely intervention and reduces their physical and social consequences. Prevalence estimates of depression approach 30% ...
Female Young Adult Adult Male Humans Machine Learning Students Universities Depression Pilot Projects Adolescent Longitudinal Studies Boosting Machine Learning Algorithms
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Comparative analysis of SWAT and SWAT coupled with XGBoost model using Optuna hyperparameter optimization for nutrient simulation: A case study in the Upper Nan River basin, Thailand.

Journal of environmental management Jun 2, 2025
Agricultural runoff leading to nitrate (NO-N) and orthophosphate (PO-P) contamination poses significant environmental and public health risks. This study integrates the Soil and Water Assessment Tool (SWAT) with eXtreme Gradient Boosting (XGBoost), o...
Water Pollutants, Chemical Soil Nutrients Thailand Nitrates Agriculture Rivers Environmental Monitoring Boosting Machine Learning Algorithms Machine Learning
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Prediction of Ligand-Receptor Interactions Based on CatBoost and Deep Forest and Their Application in Cell-Cell Communication Analysis.

Journal of chemical information and modeling May 30, 2025
Cell-to-cell communication (CCC) is prominent for cell growth and development as well as tissue and organ formation. CCC inference can help us to deeply understand cellular interplay and discover potential therapeutic targets for complex diseases. Ce...
Boosting Machine Learning Algorithms Humans Deep Learning Computational Biology Cell Communication Ligands
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Physical and mental health management for the older adult using XGBoost algorithm supported by new media technology: developing personalized health intervention plans using healthcare data from the CLHLS database.

Frontiers in public health May 30, 2025
INTRODUCTION: With the increasing aging population, there is a growing need for precise and intelligent health management solutions tailored to older adult individuals. This study proposes a comprehensive digital health management platform that integ...
Male China Boosting Machine Learning Algorithms Precision Medicine Female Aged Mental Health Artificial Intelligence Algorithms Databases, Factual Humans
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Uncovering key factors in weight loss effectiveness through machine learning.

International journal of obesity (2005) May 6, 2025
BACKGROUND/OBJECTIVES: One of the main challenges in weight loss is the dramatic interindividual variability in response to treatment. We aim to systematically identify factors relevant to weight loss effectiveness using machine learning (ML).
Humans Machine Learning Cognitive Behavioral Therapy Female Boosting Machine Learning Algorithms Weight Reduction Programs Adult Male Treatment Outcome Middle Aged Body Mass Index Exercise Obesity Weight Loss Motivation
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Cyclist crash severity modeling: A hybrid approach of XGBoost-SHAP and random parameters logit with heterogeneity in means and variances.

Journal of safety research May 5, 2025
INTRODUCTION: Across the globe, policymakers are focusing on boosting sustainable transport options, notably cycling, to foster eco-friendly urban environments. However, the persistent safety challenges cyclists face continues to hinder these efforts...
Humans Female Young Adult Adult Models, Statistical Accidents, Traffic Safety United Kingdom Male Middle Aged Adolescent Bicycling Logistic Models Boosting Machine Learning Algorithms
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Tumor grade-titude: XGBoost radiomics paves the way for RCC classification.

European journal of radiology Apr 29, 2025
This study aimed to develop and evaluate a non-invasive XGBoost-based machine learning model using radiomic features extracted from pre-treatment CT images to differentiate grade 4 renal cell carcinoma (RCC) from lower-grade tumours. A total of 102 R...
Aged, 80 and over Adult Sensitivity and Specificity Radiomics Humans Male Radiographic Image Interpretation, Computer-Assisted Female Machine Learning Middle Aged Kidney Neoplasms Reproducibility of Results Contrast Media Tomography, X-Ray Computed Carcinoma, Renal Cell Aged Neoplasm Grading Boosting Machine Learning Algorithms
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