AIMC Topic: Boosting Machine Learning Algorithms
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Exploring the complex associations between community public spaces and healthy aging: an explainable analysis using catboost and SHAP.
BMC public health
Jul 2, 2025
BACKGROUND: As global aging accelerates, community public spaces (CPS) are increasingly recognized as vital for promoting healthy aging. However, existing research often employs linear analytical methods or focuses on single health dimensions, overlo...
XAI-XGBoost: an innovative explainable intrusion detection approach for securing internet of medical things systems.
Scientific reports
Jul 1, 2025
The Internet of Medical Things (IoMT) has transformed healthcare delivery but faces critical challenges, including cybersecurity threats that endanger patient safety and data integrity. Intrusion Detection Systems (IDS) are essential for protecting I...
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...
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...
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 ...
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% ...
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...
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...
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).
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...
Tomography, X-Ray Computed
Female
Reproducibility of Results
Aged
Humans
Machine Learning
Neoplasm Grading
Radiographic Image Interpretation, Computer-Assisted
Kidney Neoplasms
Carcinoma, Renal Cell
Radiomics
Boosting Machine Learning Algorithms
Male
Aged, 80 and over
Middle Aged
Adult
Contrast Media
Sensitivity and Specificity
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