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ascopubs.org1 j

Annotations-free survival prediction with WSIs using graph convolutional neural networks.

Treatment patterns of metastatic urothelial cancer in the United States. Prediction of immune checkpoint inhibitor (ICI) response in patients with urothelial cancer (UC) by a novel RNA-based ICI ...

Yixin Zhou Advances Industrial Intelligence with AI-Based Anomaly Detection Model

A high-performance AI framework enhances anomaly detection in industrial systems using optimized Graph Deviation Networks and graph attention ...
EurekAlert!2mnd

Real-time, large-scale graph neural network inference through BingoCGN

BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...
InfoWorld1 j

The most popular neural network styles and how they work

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...
Embedded2 j

Understanding convolutional neural networks

The world of artificial intelligence (AI) is rapidly evolving, and AI is increasingly enabling applications that were previously unattainable or very difficult to implement. A subsequent article, ...
pv magazine International5mnd

Ultra-short-term PV forecasting based on convolutional neural network, long short-term memory

Scientists have created a novel probabilistic model for 5-minutes ahead PV power forecasting. The method combines a convolutional neural network with bidirectional long short-term memory, attention ...
pv magazine International1mnd

PV module fault diagnosis uses convolutional neural network

Researchers in China have created a dataset of various PV faults and normalized it to accommodate different array sizes and typologies. After testing the new approach in combination with the 1D-CNN ...