Advanced large-scale neural interfaces call for efficient algorithms to automatically process and optimally exploit the richness of their heavy continuous flow of data. In this context, we introduce here a very frugal generic single-layer Spiking Neu...
Finding process pathways in molecular simulations such as the unbinding paths of small molecule ligands from their binding sites at protein targets in a set of trajectories via unsupervised learning approaches requires the definition of a suitable si...
Pharmacokinetic (PK) parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provide quantitative characterization of tissue perfusion and permeability. However, existing deep learning methods for PK parameter estimatio...
Differential analysis in proteomics is pivotal for biomarker discovery and disease mechanism elucidation, yet traditional statistical methods are constrained by distributional assumptions and empirical fold change threshold dependencies. This study s...
Sentiment analysis has become a transformative technology in various contexts, particularly in Natural Language Processing (NLP), social media analytics, and literary analysis, as it can extract information from a wide range of texts. The advancement...
Mass spectrometry imaging (MSI) has emerged as a powerful tool for spatial metabolomics, but untargeted data analysis has proven to be challenging. When combined with isotope labeling (MSI), MSI provides insights into metabolic dynamics with high sp...
BACKGROUND: The Kidney Donor Profile Index (KDPI) is a continuous metric used to estimate the risk of allograft failure for kidneys from deceased donors. Lower KDPI scores are associated with longer post-transplant kidney function. This study aims to...
Quantum transport-based DNA sequencing is emerging as a promising technique in genetic analysis, offering fast, precise, and scalable decoding of genetic information, holding significant potential for applications in human biology and personalized me...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Aug 21, 2025
INTRODUCTION: Unsupervised deep learning methods can improve the image quality of positron emission tomography (PET) images without the need for large-scale datasets. However, these approaches typically require training a distinct network for each pa...
BACKGROUND: Acute cholangitis (AC) presents with significant clinical heterogeneity, and existing severity classifications have limited prognostic value in critically ill patients. Subtypes of AC in critically ill patients have not been investigated.
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