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Kuo-Chin Huang

Department of Family Medicine, National Taiwan University Hospital, Taipei, Taiwan

Publications

  • Research Article   
    Development of a Drug Early Warning Scoring Model for Cardiac Arrest Using Deep Learning Methods
    Author(s): Hsiao-Ko Chang, Hui-Chih Wang, Chih-Fen Huang, Feipei Lai and Kuo-Chin Huang*

    Background: In most of Taiwan’s medical institutions, congestion is a serious problem for emergency departments. Due to a lack of hospital beds, patients spend more time in emergency retention zones, which make it difficult to detect cardiac arrest. Objective: We seek to develop a Drug Early Warning Scoring Model (DEWSM), including drug injections and vital signs as these research important features. We use it to predict cardiac arrest in emergency departments via drug classification and medical experts’ suggestion. Methods: We propose this new model for detecting cardiac arrest via drug classification and by using a sliding window, and apply learning-based algorithms to time-series data for a DEWSM. To evaluate the proposed model, we use the area under the receiver operating characteristic curve (AUROC). Results: We identify the two important drug predictors: bits (int.. Read More»