Blar i forfatter Det helsevitenskapelige fakultet "Fabelo, Himar"

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    • Clinical Synthetic Data Generation to Predict and Identify Risk Factors for Cardiovascular Diseases 

      García-Vicente, Clara; Chushig-Muzo, David; Mora-Jimenez, Inmaculada; Fabelo, Himar; Gram, Inger Torhild; Løchen, Maja-Lisa; Granja, Conceição; Soguero-Ruiz, Cristina (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-01-21)
      Noncommunicable diseases are among the most significant health threats in our society, being cardiovascular diseases (CVD) the most prevalent. Because of the severity and prevalence of these illnesses, early detection and prevention are critical for reducing the worldwide health and economic burden. Though machine learning (ML) methods usually outperform conventional approaches in many domains, class ...

    • Evaluation of Synthetic Categorical Data Generation Techniques for Predicting Cardiovascular Diseases and Post-Hoc Interpretability of the Risk Factors 

      García-Vicente, Clara; Chushig-Muzo, David; Mora-Jiménez, Inmaculada; Fabelo, Himar; Gram, Inger Torhild; Løchen, Maja-Lisa; Granja, Conceição; Soguero-Ruiz, Cristina (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-03-23)
      Machine Learning (ML) methods have become important for enhancing the performance of decision-support predictive models. However, class imbalance is one of the main challenges for developing ML models, because it may bias the learning process and the model generalization ability. In this paper, we consider oversampling methods for generating synthetic categorical clinical data aiming to improve the ...