Neural networks : the official journal of the International Neural Network Society
39657531
The application of deep learning techniques to analyze brain functional magnetic resonance imaging (fMRI) data has led to significant advancements in identifying prospective biomarkers associated with various clinical phenotypes and neurological cond...
Deep learning technologies have dramatically reshaped the field of medical image registration over the past decade. The initial developments, such as regression-based and U-Net-based networks, established the foundation for deep learning in image reg...
European journal of nuclear medicine and molecular imaging
39592475
PURPOSE: Deep convolutional neural networks (CNN) hold promise for assisting the interpretation of dopamine transporter (DAT)-SPECT. For improved communication of uncertainty to the user it is crucial to reliably discriminate certain from inconclusiv...
This work proposes µGUIDE: a general Bayesian framework to estimate posterior distributions of tissue microstructure parameters from any given biophysical model or signal representation, with exemplar demonstration in diffusion-weighted magnetic reso...
This paper explores uncertainty quantification (UQ) as an indicator of the trustworthiness of automated deep-learning (DL) tools in the context of white matter lesion (WML) segmentation from magnetic resonance imaging (MRI) scans of multiple sclerosi...
Journal of chemical information and modeling
39542432
Machine learning (ML) models have become key in decision-making for many disciplines, including drug discovery and medicinal chemistry. ML models are generally evaluated prior to their usage in high-stakes decisions, such as compound synthesis or exp...
Pharmacokinetic (PK) properties of a drug are vital attributes influencing its therapeutic effectiveness, playing an important role in the drug development process. Focusing on the difficult task of predicting PK parameters, we compiled an extensive ...
Neural networks : the official journal of the International Neural Network Society
39674124
Wind power prediction is a challenging task due to the high variability and uncertainty of wind generation and weather conditions. Accurate and timely wind power prediction is essential for optimal power system operation and planning. In this paper, ...
IEEE journal of biomedical and health informatics
39504281
In semi-supervised medical image segmentation, the issue of fuzzy boundaries for segmented objects arises. With limited labeled data and the interaction of boundaries from different segmented objects, classifying segmentation boundaries becomes chall...
Visualizing surgical scenes is crucial for revealing internal anatomical structures during minimally invasive procedures. Novel View Synthesis is a vital technique that offers geometry and appearance reconstruction, enhancing understanding, planning,...