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Found 5 papers, 1 papers with code
Integration of Graph Neural Network and Neural-ODEs for Tumor Dynamic Prediction
Additionally, we show that the graph encoder is able to effectively utilize multimodal data to enhance tumor predictions.
Investigation of REFINED CNN ensemble learning for anti-cancer drug sensitivity prediction
REFINED (REpresentation of Features as Images with NEighborhood Dependencies) CNN (Convolutional Neural Network) based models have shown promising results in drug sensitivity prediction.
Kidney segmentation using 3D U-Net localized with Expectation Maximization
In this paper we propose a new framework to address some of the challenges for segmenting 3D MRI.
REFINED (REpresentation of Features as Images with NEighborhood Dependencies): A novel feature representation for Convolutional Neural Networks
We present a novel approach for representation of high dimensional feature vector in a compact image form, termed REFINED (REpresentation of Features as Images with NEighborhood Dependencies), that is conducible for convolutional neural network based deep learning.
Emotion Recognition with Machine Learning Using EEG Signals
In this research, an emotion recognition system is developed based on valence/arousal model using electroencephalography (EEG) signals.
