Enhanced Cardiovascular Disease Prediction Through a Semi-supervised Grey Ensemble Model

Lecture notes in business information processing, Journal Year: 2025, Volume and Issue: unknown, P. 218 - 231

Published: Jan. 1, 2025

Language: Английский

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Advancing cardiovascular risk prediction: A fusion of SVM models with fuzzy logic and the Sugeno integral

Biomedical Signal Processing and Control, Journal Year: 2025, Volume and Issue: 106, P. 107774 - 107774

Published: March 7, 2025

Language: Английский

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Performance Analysis and Feature Extraction for Classifying the Severity of Atopic Dermatitis Diseases

Published: Aug. 2, 2023

Atopic dermatitis, also known as eczema, is a common chronic skin condition that affects millions of people worldwide. It characterized by inflamed, itchy, and dry skin, often accompanied redness, swelling, the formation small bumps or blisters. This can vary in severity, ranging from mild intermittent to severe persistent. Precise dependable decision-making dermatologist essential ensure improved therapy risk stratification for patient. Usually, dermatologists depend on visual assessment ascertain severity score, but this approach subjective among different doctors. research aim classify atopic dermatitis based advance machine learning model such XGBoost, CatBoost, LigthGBM, Random Forest. Among evaluated models, CatBoost showed most effective reliable classification, achieved an accuracy 89%, precision 90%, recall F-Score 89%.

Language: Английский

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Air quality prediction using a novel three-stage model based on time series decomposition

Environment Development and Sustainability, Journal Year: 2024, Volume and Issue: unknown

Published: May 9, 2024

Language: Английский

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A hybrid FSRF model based on regression algorithm for diabetes medical expense prediction

Technological Forecasting and Social Change, Journal Year: 2024, Volume and Issue: 207, P. 123634 - 123634

Published: Aug. 7, 2024

Language: Английский

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