Journal of the American Medical Informatics Association : JAMIA
Sep 18, 2021
OBJECTIVE: We propose an interpretable disease prediction model that efficiently fuses multiple types of patient records using a self-attentive fusion encoder. We assessed the model performance in predicting cardiovascular disease events, given the r...
Recurrent neural networks (RNNs) have been widely used to model sequential neural dynamics ("neural sequences") of cortical circuits in cognitive and motor tasks. Efforts to incorporate biological constraints and Dale's principle will help elucidate ...
In this paper, we introduce a deep learning-based spatio-temporal continuous human gesture recognition algorithm under degraded conditions using three-dimensional (3D) integral imaging. The proposed system is shown as an efficient continuous human ge...
In this study, an automatic algorithm has been presented based on a convolutional neural network (CNN) employing U-net. An ellipsoid and an ellipse were applied for approximation of a three-dimensional sweat duct and en face sweat pore at the differe...
Proceedings of the National Academy of Sciences of the United States of America
Sep 7, 2021
We propose a deep learning-based knockoffs inference framework, DeepLINK, that guarantees the false discovery rate (FDR) control in high-dimensional settings. DeepLINK is applicable to a broad class of covariate distributions described by the possibl...
Mathematical biosciences and engineering : MBE
Sep 2, 2021
In the field of intensive aquaculture, the deterioration of water quality is one of the main factors restricting the normal growth of aquatic products. Predicting water quality in real time constitutes the theoretical basis for the evaluation, planni...
Accurate predictions of druggability and bioactivities of compounds are desirable to reduce the high cost and time of drug discovery. After more than five decades of continuing developments, quantitative structure-activity relationship (QSAR) methods...
Knowledge of the specificity of DNA-protein binding is crucial for understanding the mechanisms of gene expression, regulation and gene therapy. In recent years, deep-learning-based methods for predicting DNA-protein binding from sequence data have a...
Post-translational modifications (PTMs) play significant roles in regulating protein structure, activity and function, and they are closely involved in various pathologies. Therefore, the identification of associated PTMs is the foundation of in-dept...
In recent years, single-cell RNA sequencing (scRNA-seq) technologies have been widely adopted to interrogate gene expression of individual cells; it brings opportunities to understand the underlying processes in a high-throughput manner. Deep embedde...
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