Mei, Y.;                     Jin, Z.;                     Ma, W.;                     Ma, Y.;                     Deng, N.;                     Fan, Z.;                     Wei, S.    
        Optimizing Acute Coronary Syndrome Patient Treatment: Leveraging Gated Transformer Models for Precise Risk Prediction and Management. Bioengineering 2024, 11, 551.
    https://doi.org/10.3390/bioengineering11060551
    AMA Style
    
                                Mei Y,                                 Jin Z,                                 Ma W,                                 Ma Y,                                 Deng N,                                 Fan Z,                                 Wei S.        
                Optimizing Acute Coronary Syndrome Patient Treatment: Leveraging Gated Transformer Models for Precise Risk Prediction and Management. Bioengineering. 2024; 11(6):551.
        https://doi.org/10.3390/bioengineering11060551
    
    Chicago/Turabian Style
    
                                Mei, Yingxue,                                 Zicai Jin,                                 Weiguo Ma,                                 Yingjun Ma,                                 Ning Deng,                                 Zhiyuan Fan,                                 and Shujun Wei.        
                2024. "Optimizing Acute Coronary Syndrome Patient Treatment: Leveraging Gated Transformer Models for Precise Risk Prediction and Management" Bioengineering 11, no. 6: 551.
        https://doi.org/10.3390/bioengineering11060551
    
    APA Style
    
                                Mei, Y.,                                 Jin, Z.,                                 Ma, W.,                                 Ma, Y.,                                 Deng, N.,                                 Fan, Z.,                                 & Wei, S.        
        
        (2024). Optimizing Acute Coronary Syndrome Patient Treatment: Leveraging Gated Transformer Models for Precise Risk Prediction and Management. Bioengineering, 11(6), 551.
        https://doi.org/10.3390/bioengineering11060551