Islam Mohaimenul, Yang Hsuan-Chia, Nguyen Phung-Anh, Wang Yu-Hsiang, Poly Tahmina Nasrin, Li Yu-Chuan Jack
Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan.
International Center for Health Information Technology, Taipei Medical University, Taipei, Taiwan.
Stud Health Technol Inform. 2020 Jun 16;270:1241-1242. doi: 10.3233/SHTI200382.
We developed a deep learning approach for accurate prediction of PCA patients one year earlier with minimal features from electronic health records. The area under the receiver operating curve for prediction of PCA was 0.94. Moreover, the sensitivity and specificity of CNN were 0.87 and 0.88, respectively.
我们开发了一种深度学习方法，通过电子健康记录中的最少特征，提前一年准确预测PCA患者。预测PCA的受试者工作特征曲线下面积为0.94。此外，CNN的敏感性和特异性分别为0.87和0.88。
