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  1. 1
    Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score

    Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score by Mirza Rizwan, Sajid

    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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  2. 2
    A Risk Assessment of Transmission Line Overload Based on MLSI/PSO

    A Risk Assessment of Transmission Line Overload Based on MLSI/PSO by Ruhaizad, Ishak, Ali, A., Nazir, Muhammad S., Malik, Muhammad Z.

    Published 2019
    “…Based on the traditional partial swarm optimization algorithm, the corresponding weights are selected according to the influence factors of each input quantity, and the calculation accuracy of the traditional point estimation method is improved to realize the overload risk assessment of transmission lines. …”
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  3. 3
    Extreme air pollutant data analysis using classical and Bayesian approaches

    Extreme air pollutant data analysis using classical and Bayesian approaches by Mohd Amin, Nor Azrita

    Published 2015
    “…Literature on Bayesian extremes based on MCMC techniques are dealing with either Gibbs sampling method or MH method, or the combination of both methods. …”
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  4. 4
    Data mining techniques for disease risk prediction model: A systematic literature review

    Data mining techniques for disease risk prediction model: A systematic literature review by Ahmad W.M.T.W., Ghani N.L.A., Drus S.M.

    Published 2023
    Conference Paper
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  5. 5
    Steady state security analysis using artificial neural network

    Steady state security analysis using artificial neural network by Mohd Nor, Nurul Huda

    Published 2008
    “…The artificial neural network (ANN)-based approach for contingency ranking. A set of feed forward neural networks are developed to estimate the voltage stability level at different load conditions for the selected contingencies. …”
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  6. 6
    Prediction of breast cancer relapse time in continuous scale based on type-2 TSK fuzzy model

    Prediction of breast cancer relapse time in continuous scale based on type-2 TSK fuzzy model by Mahmoudian, Sayed Hamid

    Published 2010
    “…In addition, K-fold Cross Validation, B632 and B632+ methods have been used for error estimation. In the first objective of the thesis, a lemma has been proven and a new hybrid algorithm based on Fuzzy Association Rule Mining has been proposed to gather some selected genes and generate fuzzy rules for classification. …”
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  7. 7
    Radiation dose, cancer risk and diagnostic performance of computed tomography pulmonary angiography examination

    Radiation dose, cancer risk and diagnostic performance of computed tomography pulmonary angiography examination by Haspi Harun, Hanif

    Published 2021
    “…Hence, this study aims to evaluate the radiation dose, cancer risk and image diagnostic performance of CTPA examination regarding primary and secondary optimization such as iterative reconstruction (IR) algorithm, tube potential and pitch factor selection. …”
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  8. 8
    A framework for automatic modelling of survival using fuzzy inference.

    A framework for automatic modelling of survival using fuzzy inference. by Hamdan, Hazlina, Garibaldi, Jonathan M.

    Published 2012
    “…After the initialisation of the fuzzy inference structure, the replication data (until time to event) will be subject to be trained using the gradient descent and nonnegative least square algorithm to estimate the conditional event probability. …”
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  9. 9
    Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region

    Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region by Bhattacharya S., Ali T., Chakravortti S., Pal T., Majee B.K., Mondal A., Pande C.B., Bilal M., Rahman M.T., Chakrabortty R.

    Published 2025
    “…In recent years, statistical methods and, increasingly, machine learning-based approaches have gained popularity for landslide susceptibility modeling. …”
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  10. 10
    Modelling and Forecasting the Kuala Lumpur Composite Index Rate of Returns Using Generalised Autoregressive Conditional Heteroscedasticity Models

    Modelling and Forecasting the Kuala Lumpur Composite Index Rate of Returns Using Generalised Autoregressive Conditional Heteroscedasticity Models by Abdul Muthalib, Maiyastri

    Published 2004
    “…The EM algorithm is applied to split the heterogeneous data, and the estimated parameters are used to correct the outlying data using the Mahalanobis Distance. …”
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  11. 11
    Unified framework for spam detection and risk assessment in short message communication media / Adewole Kayode Sakariyah

    Unified framework for spam detection and risk assessment in short message communication media / Adewole Kayode Sakariyah by Adewole Kayode, Sakariyah

    Published 2018
    “…Existing content-based methods for spam detection degraded in performance due to many factors. …”
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  12. 12
    Groundwater quality assessment and optimization of monitored wells using multivariate geostatistical techniques in Amol-Babol Plain, Iran

    Groundwater quality assessment and optimization of monitored wells using multivariate geostatistical techniques in Amol-Babol Plain, Iran by Narany, Tahoora Sheikhy

    Published 2015
    “…DRASTIC model was applied as a vulnerability assessment method based on the physical environmental aquifer parameters for assessing potential risk zone of aquifer to contamination, which showed more than 88% of the total area was classified as low to moderate risk to pollutant. …”
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  13. 13
    Determining malaria risk factors in Abuja, Nigeria using various statistical approaches

    Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

    Published 2018
    “…Therefore, this was not incorporated in BBN models. Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
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  14. 14
    A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal

    A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal by Aymen Taher , Ahmed al-Ashwal

    Published 2019
    “…Features are then enhanced by using Tree-based feature selection to reduce the size of each feature and, therefore, enhance classification performance. …”
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  15. 15
    A comparative study on aviation arrival delay prediction using machine learning methods

    A comparative study on aviation arrival delay prediction using machine learning methods by Chew, Pui Ting

    Published 2023
    “…Considering the afore-mentioned model building methods for both approaches, ANN model using stepwise regression approach performs the best for flight arrival delay prediction based on F1 score. …”
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  16. 16
    Credit scoring for Cooperative of financial services using logistic regression estimated by genetic algorithm

    Credit scoring for Cooperative of financial services using logistic regression estimated by genetic algorithm by Mustafa, Mamat, Sukono, Firman, Asep, Sholahuddin

    Published 2014
    “…In this paper the analysis of credit scoring is done using logistic regression model, which is estimated using genetic algorithms. As a numerical illustration, the method used to analyze the credit scoring on a cooperative of financial services in Indonesia. …”
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  17. 17
    Risk assessment for safety and health algorithm for building construction in Oman

    Risk assessment for safety and health algorithm for building construction in Oman by Al-Anbari, Saud Said

    Published 2015
    “…The RASH algorithm is defined by overall risk, which is equivalent to the sum of Risk Safety Safety, Risk Safety Health, Risk Health Safety, and Risk Health Health. …”
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  18. 18
    Bayesian logistic regression model on risk factors of type 2 diabetes mellitus

    Bayesian logistic regression model on risk factors of type 2 diabetes mellitus by Chiaka, Emenyonu Sandra

    Published 2016
    “…The significant variables determined by maximum likelihood method were then estimated using the BLR method. The BLR approach via Gibbs sampler and the random walk metropolis algorithm suggests that family history of diabetes, waist circumference and the body mass index are the significant risk factors associated with the type 2 diabetes mellitus. …”
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  19. 19
    Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model

    Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model by Elfaki, Faiz. A. M.

    Published 2000
    “…The Expectation Maximization (EM) was considered to obtain the estimate of the parameters. These estimates were then compared to the Newton-Raphson iteration method. …”
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  20. 20
    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman

    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

    Published 2019
    “…Block Matching Algorithm (BMA) is a technique used to minimize the computational complexity of motion estimation in video coding application. …”
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