AIMC Topic: Boosting Machine Learning Algorithms

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Integrating AI for infectious disease prediction: A hybrid ANN-XGBoost model for leishmaniasis in Pakistan.

Acta tropica Apr 23, 2025
Addressing leishmaniasis infection remains a substantial challenge in KP-Pakistan due to the increased infection prevalence. Understanding its spreading tool offerings is a major challenge. We essentially design effective approaches to pinpoint its e...
Boosting Machine Learning Algorithms Prevalence Models, Statistical Incidence Pakistan Humans Leishmaniasis Forecasting
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Source apportionment of PM particles in the urban atmosphere using PMF and LPO-XGBoost.

Environmental research Apr 22, 2025
Atmospheric particulate matter (PM), as a leading part of air pollution, affects health in many ways. Thus, identifying and quantifying the contribution of atmospheric particulate matter sources of PM is vital for developing effective air quality man...
Cities Models, Theoretical Air Pollution Environmental Monitoring Boosting Machine Learning Algorithms Particulate Matter Europe Atmosphere Air Pollutants
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Unique Microbial Characterisation of Oesophageal Squamous Cell Carcinoma Patients with Different Dietary Habits Based on Light Gradient Boosting Machine Learning Classifier.

Nutrients Apr 14, 2025
: The microbiome plays an important role in cancer, but the relationship between dietary habits and the microbiota in oesophageal squamous cell carcinoma (ESCC) is not clear. The aim of this study is to explore the complex relationship between the mi...
Boosting Machine Learning Algorithms Bacteria Gastrointestinal Microbiome RNA, Ribosomal, 16S Feeding Behavior Esophageal Squamous Cell Carcinoma Humans Esophageal Neoplasms Male Machine Learning Microbiota Middle Aged Female Diet Aged
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Comparative study of XGBoost and logistic regression for predicting sarcopenia in postsurgical gastric cancer patients.

Scientific reports Apr 14, 2025
The use of machine learning (ML) techniques, particularly XGBoost and logistic regression, to predict sarcopenia among postsurgical gastric cancer patients has gained significant attention in recent research. Sarcopenia, characterized by the progress...
Retrospective Studies Female Risk Factors Humans Machine Learning Middle Aged Postoperative Complications China ROC Curve Aged Stomach Neoplasms Male Boosting Machine Learning Algorithms Logistic Models Sarcopenia Gastrectomy
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Prediction of cardiovascular disease based on multiple feature selection and improved PSO-XGBoost model.

Scientific reports Apr 11, 2025
Cardiovascular disease is a common disease that threatens human health. In order to predict it more accurately, this paper proposes a cardiovascular disease prediction model that combines multiple feature selection, improved particle swarm optimizati...
ROC Curve Area Under Curve Boosting Machine Learning Algorithms Humans Cardiovascular Diseases
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Advancing enterprise risk management with deep learning: A predictive approach using the XGBoost-CNN-BiLSTM model.

PloS one Apr 3, 2025
Enterprise risk management is a key element to ensure the sustainable and steady development of enterprises. However, traditional risk management methods have certain limitations when facing complex market environments and diverse risk events. This s...
Risk Management Humans Boosting Machine Learning Algorithms Neural Networks, Computer Deep Learning
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Explainable SHAP-XGBoost models for pressure injuries among patients requiring with mechanical ventilation in intensive care unit.

Scientific reports Mar 22, 2025
pressure injuries are significant concern for ICU patients on mechanical ventilation. Early prediction is crucial for enhancing patient outcomes and reducing healthcare costs. This study aims to develop a predictive model using machine learning techn...
Risk Factors Aged Male Algorithms Humans Pressure Ulcer Middle Aged Machine Learning Intensive Care Units Boosting Machine Learning Algorithms Respiration, Artificial Female ROC Curve
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Interpretable machine learning for thyroid cancer recurrence predicton: Leveraging XGBoost and SHAP analysis.

European journal of radiology Mar 14, 2025
PURPOSE: For patients suffering from differentiated thyroid cancer (DTC), several clinical, laboratory, and pathological features (including patient age, tumor size, extrathyroidal extension, or serum thyroglobulin levels) are currently used to ident...
Adult Sensitivity and Specificity Biomarkers, Tumor Risk Assessment Thyroid Neoplasms Male Middle Aged Reproducibility of Results Risk Factors Aged Prognosis Neoplasm Recurrence, Local Retrospective Studies Humans Germany Female Machine Learning Boosting Machine Learning Algorithms
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Sustainable extraction of phytochemicals from Mentha arvensis using supramolecular eutectic solvent via microwave Irradiation: Unveiling insights with CatBoost-Driven feature analysis.

Ultrasonics sonochemistry Mar 4, 2025
The present study revealed the higher extraction potential of sustainable choline chloride (ChCl) and ethylene glycol (EG) based deep eutectic solvent (DES) from Mentha arvensis via microwave irradiation. The categorical boosting (CatBoost) machine l...
Mentha Solvents Chemical Fractionation Boosting Machine Learning Algorithms Machine Learning Microwaves Biomass Deep Eutectic Solvents Phytochemicals
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Enhancing e-waste management: a novel light gradient AdaBoost support vector classification approach.

Environmental monitoring and assessment Feb 27, 2025
The global consequences of electronic waste significantly affect the environment and human health. Accurate classification is essential for effective recycling and management to mitigate serious environmental harm caused by improper disposal. However...
Support Vector Machine Waste Management Boosting Machine Learning Algorithms Algorithms Electronic Waste
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