Results 131 to 140 of about 10,729 (204)
Scanner‐agnostic artificial intelligence approach for fast bone scintigraphy
Journal of Applied Clinical Medical Physics, Volume 27, Issue 8, August 2026.Abstract Purpose Current bone scintigraphy protocols often demand full‐count, 10–15 min scans to preserve image quality, and existing deep‐learning (DL) denoisers typically need to be retrained or retuned for each camera manufacturer. We introduce a scanner‐agnostic adaptive‐diffusion U‐Net designed to reconstruct diagnostic‐grade images from half‐time
Vinicius de Oliveira Menezes +9 more
wiley +1 more source
Erratum: Estimating the spectrum in computed tomography via Kullback-Leibler divergence constrained optimization. [Med. Phys. 46(1), p. 81-92 (2019)]. [PDF]
Med Phys, 2020 Ha W +4 more
europepmc +1 more source
Advanced Science, Volume 13, Issue 43, 3 August 2026.STAID is a unified deep learning framework that couples iterative pseudo‐spot refinement with neural network training through a feedback loop and exploits gene co‐expression information to model higher‐order interactions, achieving accurate and robust cell‐type deconvolution in spatial transcriptomics.
Jixin Liu +5 more
wiley +1 more source
CNS Neuroscience &Therapeutics, Volume 32, Issue 8, August 2026.Insomnia disorder involves a dual dysregulation pattern: reduced frontal delta‐beta coupling (impaired control) and enhanced occipital theta‐beta coupling (heightened reactivity). These mechanisms underlie emotional susceptibility and negative attentional bias.
Siyu Li +6 more
wiley +1 more source
Lost in Translation? Risk‐Adjusting RMSE for Economic Forecast Performance
Journal of Forecasting, Volume 45, Issue 5, Page 2587-2605, August 2026.ABSTRACT When used for parameter optimization and/or model selection, traditional mean squared error (MSE)–based measures of forecast accuracy often exhibit a weak or even negative correlation with the economic value of return forecasts measured by, for example, the Sharpe ratios of the resulting portfolios.
Lukas Salcher +2 more
wiley +1 more source
Human Brain Mapping, Volume 47, Issue 11, 01 August 2026.Using structural MRI data from over 2700 participants, this large‐scale study shows that major depressive disorder exhibits distinct, feature‐specific alterations across multiple brain structural networks. These changes are already present in first‐episode, drug‐naive patients and allow effective differentiation between individuals with depression and ...
Xuetian Sun +129 more
wiley +1 more source
Scaling and Uncertainty in Soil Moisture Modelling: A Probabilistic Deep Learning Perspective
Hydrological Processes, Volume 40, Issue 8, August 2026.A probabilistic Gaussian Mixture Long Short‐Term Memory framework is used to investigate soil moisture dynamics across the continental United States using meteorological forcings and physiographic attributes. Predictions are evaluated at unseen International Soil Moisture Network sites to ensure realistic regional transfer.
Balazs Bischof, Erwin Zehe, Ralf Loritz
wiley +1 more source
Limnology and Oceanography, Volume 71, Issue 8, August 2026.Abstract Groundwater dissolved oxygen (DO) variability in coastal systems remains poorly understood despite its importance for biogeochemical cycling and ecosystem modeling. This study investigates temporal variability in groundwater DO and its hydro‐climatic drivers across timescales (hourly to seasonal) in a coastal floodplain at Beaver Creek ...
Emilio Grande +5 more
wiley +1 more source
Individual brain metabolic connectome indicator based on Kullback-Leibler Divergence Similarity Estimation predicts progression from mild cognitive impairment to Alzheimer's dementia. [PDF]
Eur J Nucl Med Mol Imaging, 2020 Wang M +10 more
europepmc +1 more source
Statistical Analysis and Data Mining: An ASA Data Science Journal, Volume 19, Issue 4, August 2026.ABSTRACT Simplicial–simplicial regression concerns statistical modeling scenarios in which both the predictors and the responses contain vectors constrained to lie on the simplex. Fiksel et al. introduced a transformation‐free linear regression framework for this setting, wherein the regression coefficients are estimated by minimizing the Kullback ...
Michail Tsagris, Omar Alzeley
wiley +1 more source