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Ji-Han Liu

Graduate institute of Networking and Multimedia, National Taiwan University, Taipei, Taiwan

Publications

  • Research Article   
    Early Prediction for Fatty Liver Disease with Eigenvector-Based Feature Selections for Model Performance Enhancement
    Author(s): Ji-Han Liu*, Kuo-Chin Huang and Feipei Lai

    Objectives: This study is aimed to achieve the rapid optimization of the input feature subset that satisfies the expert’s point of view and enhance the prediction performance of the early prediction model for fatty liver disease (FLD). Methods: We explore a large-scale and high-dimension dataset coming from a northern Taipei Health Screening Center in Taiwan, and the dataset includes data of 12,707 male and 10,601 female patients processed from around 500,000 records from year 2009 to 2016. We propose three eigenvector-based feature selections taking the Intersection of Union (IoU) and the Coverage to determine the sub-optimal subset of features with the highest IoU and the Coverage automatically, use various long short-term memory (LSTM) related classifiers for FLD prediction, and evaluate the model performance b.. Read More»