Computer methods and programs in biomedicine
Aug 16, 2023
BACKGROUND AND OBJECTIVE: As an advanced technique, immunofluorescence (IF) is one of the most widely-used medical image for nephropathy diagnosis, due to its ease of acquisition with low cost. In practice, the clinically collected IF images are comm...
Flood risk assessment is a key step in flood management and mitigation, and flood risk maps provide a quantitative measure of flood risk. Therefore, integration of deep learning - an updated version of machine learning techniques - and multi-criteria...
Neural networks : the official journal of the International Neural Network Society
Aug 16, 2023
The rise of graph representation learning as the primary solution for many different network science tasks led to a surge of interest in the fairness of this family of methods. Link prediction, in particular, has a substantial social impact. However,...
Journal of computational biology : a journal of computational molecular cell biology
Aug 16, 2023
Spiking neural network (SNN) simulators play an important role in neural system modeling and brain function research. They can help scientists reproduce and explore neuronal activities in brain regions, neuroscience, brain-like computing, and other f...
Accurate prediction of surface subsidence is of significance for analyzing the pattern of mining-induced surface subsidence, and for mining under buildings, railways, and water bodies. To address the problem that the existing prediction models ignore...
Accurate prediction of wave overtopping at sea defences remains central to the protection of lives, livelihoods, and infrastructural assets in coastal zones. In addressing the increased risks of rising sea levels and more frequent storm surges, robus...
OBJECTIVES: To develop a deep learning methodology that distinguishes early from late stages of avascular necrosis of the hip (AVN) to determine treatment decisions.
PURPOSE: To mitigate the problem of noisy parameter maps with high uncertainties by casting parameter mapping as a denoising task based on Deep Image Priors.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Aug 15, 2023
Deep learning (DL) shows notable success in biomedical studies. However, most DL algorithms work as black boxes, exclude biomedical experts, and need extensive data. This is especially problematic for fundamental research in the laboratory, where oft...
Journal of chemical information and modeling
Aug 15, 2023
Oral bioavailability is a pharmacokinetic property that plays an important role in drug discovery. Recently developed computational models involve the use of molecular descriptors, fingerprints, and conventional machine-learning models. However, dete...
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