AIMC Topic: Boosting Machine Learning Algorithms

Clear Filters Showing 1 to 10 of 54 articles

Evaluation of coseismic landslide susceptibility by combining Newmark model and XGBoost algorithm.

PloS one Aug 11, 2025
Coseismic landslides are among the most perilous geological disasters in hilly places after earthquakes. Precise assessment of coseismic landslide susceptibility is crucial for forecasting the effects of landslides and alleviating subsequent tragedie...
Machine Learning Disasters Boosting Machine Learning Algorithms Landslides Earthquakes Algorithms Models, Theoretical Monte Carlo Method
View on PubMed DOI

Non-invasive acoustic classification of adult asthma using an XGBoost model with vocal biomarkers.

Scientific reports Aug 6, 2025
Traditional diagnostic methods for asthma, a widespread chronic respiratory illness, are often limited by factors such as patient cooperation with spirometry. Non-invasive acoustic analysis using machine learning offers a promising alternative for ob...
Acoustics Voice Humans Male Boosting Machine Learning Algorithms Middle Aged Machine Learning Female Case-Control Studies Biomarkers Young Adult Adult Asthma
View on PubMed DOI

Predicting geriatric environmental safety perception assessment using LightGBM and SHAP framework.

Scientific reports Jul 28, 2025
Global population aging highlights the need to understand how the elderly perceive safety in urban public spaces. This study used image semantic segmentation to identify key visual elements from panoramic images. A dataset was created by combining ma...
Safety Parks, Recreational Perception Boosting Machine Learning Algorithms Aged Aged, 80 and over Male Humans Female
View on PubMed DOI

AI-driven skin cancer detection from smartphone images: A hybrid model using ViT, adaptive thresholding, black-hat transformation, and XGBoost.

PloS one Jul 28, 2025
Skin cancer is a significant global public health issue, with millions of new cases identified each year. Recent breakthroughs in artificial intelligence, especially deep learning, possess considerable potential to enhance the accuracy and efficiency...
Female Melanoma Skin Neoplasms Carcinoma, Basal Cell Humans Artificial Intelligence Algorithms Image Processing, Computer-Assisted Smartphone Boosting Machine Learning Algorithms Keratosis, Seborrheic Male Middle Aged Deep Learning
View on PubMed DOI

DNA sequence classification for diabetes mellitus using NuSVC and XGBoost: A comparative.

PloS one Jul 18, 2025
Diabetes Mellitus is a global health concern, characterized by high blood sugar levels over a prolonged period, leading to severe complications if left unmanaged. The early identification of individuals at risk is critical for effective intervention ...
Machine Learning Diabetes Mellitus Support Vector Machine Sequence Analysis, DNA Boosting Machine Learning Algorithms Humans
View on PubMed DOI

Prediction of gastrointestinal hemorrhage in cardiology inpatients using an interpretable XGBoost model.

Scientific reports Jul 12, 2025
Gastrointestinal bleeding (GIB) occurs more frequently in cardiovascular patients than in the general population, significantly affecting morbidity and mortality. However, existing predictive models often lack sufficient accuracy and interpretability...
Hemoglobins Gastrointestinal Hemorrhage Boosting Machine Learning Algorithms Middle Aged Risk Assessment Machine Learning Inpatients Retrospective Studies Female Risk Factors Humans Aged Aged, 80 and over Male
View on PubMed DOI

Prediction of three-year all-cause mortality in patients with heart failure and atrial fibrillation using the CatBoost model.

BMC cardiovascular disorders Jul 4, 2025
BACKGROUND: Heart failure and atrial fibrillation (HF-AF) frequently coexist, resulting in complex interactions that substantially elevate mortality risk. This study aimed to develop and validate a machine learning (ML) model predicting the 3-year al...
Reproducibility of Results Risk Factors Aged Aged, 80 and over Heart Failure Male Decision Support Techniques Atrial Fibrillation Middle Aged Prognosis Time Factors Boosting Machine Learning Algorithms Risk Assessment Retrospective Studies Predictive Value of Tests Humans Female Cause of Death Machine Learning
View on PubMed DOI

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...
Healthy Aging Humans Middle Aged Machine Learning Aged Female China Aged, 80 and over Residence Characteristics Male Boosting Machine Learning Algorithms
View on PubMed DOI

Nonlinear association between visceral fat metabolism score and heart failure: insights from LightGBM modeling and SHAP-Driven feature interpretation in NHANES.

BMC medical informatics and decision making Jul 1, 2025
OBJECTIVE: Using 2005-2018 NHANES data, this study examined the association between the visceral fat metabolism score (METS-VF) and heart failure (HF) prevalence in U.S. adults, leveraging machine learning (LightGBM/XGBoost) and SHAP for classficatio...
Nutrition Surveys Aged Intra-Abdominal Fat United States Humans Adult Boosting Machine Learning Algorithms Heart Failure Machine Learning Male Female Middle Aged
View on PubMed DOI

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...
Boosting Machine Learning Algorithms Delivery of Health Care Humans Internet of Things Algorithms Computer Security
View on PubMed DOI
Popular Topics
Recent Journals