Replay is the reactivation of one or more neural patterns that are similar to the activation patterns experienced during past waking experiences. Replay was first observed in biological neural networks during sleep, and it is now thought to play a cr...
Our real-time actions in everyday life reflect a range of spatiotemporal dynamic brain activity patterns, the consequence of neuronal computation with spikes in the brain. Most existing models with spiking neurons aim at solving static pattern recogn...
Journal of the American Medical Informatics Association : JAMIA
Oct 12, 2021
OBJECTIVE: To develop an end-to-end deep learning framework based on a protein-protein interaction (PPI) network to make synergistic anticancer drug combination predictions.
For 177Lu-DOTATATE treatments, dosimetry based on manual kidney segmentation from computed tomography (CT) is accurate but time consuming and might be affected by misregistration between CT and SPECT images. This study develops a convolution neural n...
Deciphering the sequence-function relationship encoded in enhancers holds the key to interpreting non-coding variants and understanding mechanisms of transcriptomic variation. Several quantitative models exist for predicting enhancer function and und...
Since lung nodules on computed tomography images can have different shapes, contours, textures or locations and may be attached to neighboring blood vessels or pleural surfaces, accurate segmentation is still challenging. In this study, we propose an...
The Journal of pharmacy and pharmacology
Oct 7, 2021
OBJECTIVES: As a common step in the herbal medicine production process, percolation usually lacks effective process monitoring methods and is often conducted with fixed process parameters. In this study, an in-line ultraviolet (UV) spectroscopy was u...
Convolutional neural networks have become the state-of-the-art method for image classification in the last 10 years. Despite the fact that they achieve superhuman classification accuracy on many popular datasets, they often perform much worse on more...
Underwater acoustic target recognition based on ship-radiated noise is difficult owing to the complex marine environment and the interference by multiple targets. As an important technology for target recognition, deep-learning has high accuracy but ...
The Journal of the Acoustical Society of America
Oct 1, 2021
We train an object detector built from convolutional neural networks to count interference fringes in elliptical antinode regions in frames of high-speed video recordings of transient oscillations in Caribbean steelpan drums, illuminated by electroni...
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