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...
Humans Models, Statistical Pakistan Leishmaniasis Boosting Machine Learning Algorithms Forecasting Prevalence Incidence
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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...
Esophageal Neoplasms Microbiota Feeding Behavior Bacteria Gastrointestinal Microbiome RNA, Ribosomal, 16S Esophageal Squamous Cell Carcinoma Boosting Machine Learning Algorithms Machine Learning Female Aged Male Middle Aged Diet Humans
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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...
Machine Learning Retrospective Studies Female Humans China Male ROC Curve Middle Aged Logistic Models Sarcopenia Postoperative Complications Gastrectomy Risk Factors Boosting Machine Learning Algorithms Aged Stomach Neoplasms
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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...
Area Under Curve Boosting Machine Learning Algorithms Humans Cardiovascular Diseases ROC Curve
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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...
Humans Risk Management Neural Networks, Computer Boosting Machine Learning Algorithms 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 Intensive Care Units Female Humans Middle Aged Machine Learning Pressure Ulcer Respiration, Artificial Boosting Machine Learning Algorithms 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...
Retrospective Studies Female Reproducibility of Results Risk Factors Aged Adult Humans Machine Learning Prognosis Neoplasm Recurrence, Local Middle Aged Germany Sensitivity and Specificity Risk Assessment Boosting Machine Learning Algorithms Biomarkers, Tumor Thyroid Neoplasms Male
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Identification of Fusarium sambucinum species complex by surface-enhanced Raman spectroscopy and XGBoost algorithm.

Food chemistry Mar 12, 2025
Rapid and reliable identification of Fusarium fungi is crucial, due to their role in food spoilage and potential toxicity. Traditional identification methods are often time-consuming and resource-intensive. This study explores the use of surface-enha...
Fusarium Hordeum Boosting Machine Learning Algorithms Spectrum Analysis, Raman
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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...
Deep Eutectic Solvents Boosting Machine Learning Algorithms Solvents Chemical Fractionation Microwaves Phytochemicals Machine Learning Biomass Mentha
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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...
Electronic Waste Algorithms Support Vector Machine Waste Management Boosting Machine Learning Algorithms
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