• An adaptive Laplacian weight random forest imputation for imbalance and mixed-type data 

      Ren, Lijuan; Seklouli, Aicha Sekhari; Zhang, Haiqing; Wang, Tao; Bouras, Abdelaziz ( Elsevier , 2023 , Article)
      As the application of information technology in the medical field is resulting in a large amount of medical data. As early withdrawal and refusal of participants, there are a lot of missing values in medical data. Although ...
    • Hypertension Prediction Using Optimal Random Forest and Real Medical Data 

      Ren, Lijuan; Seklouli, Aicha Sekhari; Wang, Tao; Zhang, Haiqing; Bouras, Abdelaziz ( Institute of Electrical and Electronics Engineers Inc. , 2022 , Conference Paper)
      Long-lasting and difficult-to-treat, hypertension frequently leads to serious and life-threatening diseases. As a result, early risk assessment and prevention of hypertension are crucial. The majority of research currently ...
    • Stacking-based multi-objective ensemble framework for prediction of hypertension 

      Ren, Lijuan; Zhang, Haiqing; Sekhari Seklouli, Aicha; Wang, Tao; Bouras, Abdelaziz ( Elsevier , 2023 , Article)
      Hypertension is a common health problem that is costly to treat, difficult to control, and frequently results in serious and fatal disorders like cardiovascular disease (CVD) and stroke. The main objective of this work was ...