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Found 3 papers, 1 papers with code
Multimodal Neurodegenerative Disease Subtyping Explained by ChatGPT
Thus, we propose a multimodal framework that uses early-stage indicators such as imaging, genetics and clinical assessments to classify AD patients into subtypes at early stages.
Noise Entangled GAN For Low-Dose CT Simulation
We propose a Noise Entangled GAN (NE-GAN) for simulating low-dose computed tomography (CT) images from a higher dose CT image.
Quadratic Autoencoder (Q-AE) for Low-dose CT Denoising
Inspired by complexity and diversity of biological neurons, our group proposed quadratic neurons by replacing the inner product in current artificial neurons with a quadratic operation on input data, thereby enhancing the capability of an individual neuron.
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