Abstract: Heart diseases (CVDs) persist a precede cause of fatality rate worldwide, necessitating accurate and explainable prediction model for early diagnosis and intercession. This study inquire the ...
Objective: We aimed to explore the perspectives of primary care HCPs on managing MLTC and their attitudes toward using AI tools to support clinical decision-making in MLTC care. Methods: In total, 20 ...
There is indeed a vast literature on the design and analysis of decision tree algorithms that aim at optimizing these parameters. This paper contributes to this important line of research: we propose ...
ABSTRACT: This paper proposes a hybrid AI framework that integrates technical indicators, fundamental data, and financial news sentiment into a stacked ensemble learning model. The ensemble combines ...
This research aims to comparatively investigate, evaluate and develop various prediction models by using Artificial Neural Network (ANN), Support Vector Machine (SVM), Random Forest, Adaptively ...
Objective: This study compared a conventional logistic regression model with machine learning (ML) models using demographic and clinical data to predict outcomes at 2 and 6 months of treatment for MDR ...
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