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Data mining techniques for disease risk prediction model: A systematic literature review
Published 2023Conference Paper -
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Loan default prediction using machine learning algorithms: a systematic literature review 2020 -2023
Published 2024“…It critically examines the transition from traditional statistical models to advanced ML techniques in assessing credit risk, with a focus on the banking sector's need for reliable default prediction methods. …”
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Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score
Published 2021“…Further, it focuses on the development of various forms of local risk prediction models and simple heart risk scores using non-laboratory features and machine learning (ML) algorithms. …”
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Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm
Published 2025“…This performance is validated through rigorous comparative assessments against various classification algorithms and state-of-the-art methods, revealing notable advantages in terms of predictive precision, computational efficiency, and adaptability to real-world clinical scenarios. …”
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Poverty risk prediction based on socioeconomic factors using machine learning approach
Published 2025“…The process of classifying individuals or households that may be at risk of poverty can be time consuming and less accurate in relation to traditional methods like Poverty Line Income (PLI). …”
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Integrated deep learning for cardiovascular risk assessment and diagnosis: An evolutionary mating algorithm-enhanced CNN-LSTM
Published 2025“…The model predicts both a continuous risk score and a binary diagnostic outcome, supporting both quantitative assessment and early clinical decision-making. …”
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Artificial neural network model for predicting windstorm intensity and the potential damages / Mohd Fatruz Bachok
Published 2019“…A predictive model was developed to provide a mechanism that can be regionally simulated, and predict low or high risk windstorm, its possible location, time, duration of the risk, intensity as well as potential damages. …”
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Predicting bankruptcy using ant colony optimization / Nur Syafiqah Abdul Ghani
Published 2021“…The results have shown that the Ant Colony Optimization Algorithm produced a better predictive accuracy. Therefore, it is confirmed that the Ant Colony Optimization Algorithm produces the most accurate result in predicting bankruptcy. …”
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New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Published 2023“…However, the big problem with prediction is data imbalance and low performance classification algorithms. …”
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New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Published 2023“…However, the big problem with prediction is data imbalance and low performance classification algorithms. …”
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New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Published 2023“…However, the big problem with prediction is data imbalance and low performance classification algorithms. …”
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Predicting Customer Behaviour on Buying Life Insurance using Machine Learning
Published 2026journal::journal article -
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A Fusion-Based Framework For Explainable Suicide Attempt Prediction
Published 2024“…The proposed work aims to analyse an explainable learning algorithms for predicting suicide attempts, propose an ontology model for semantically representing the classification risk of suicide attempts and propose an explanation generation algorithm by combining predictions from explainable machine learning and ontology models. …”
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New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
Published 2023“…However, the big problem with prediction is data imbalance and low performance classification algorithms. …”
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New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
Published 2023“…However, the big problem with prediction is data imbalance and low performance classification algorithms. …”
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New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
Published 2023“…However, the big problem with prediction is data imbalance and low performance classification algorithms. …”
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New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
Published 2023“…However, the big problem with prediction is data imbalance and low performance classification algorithms. …”
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