Latest AI and machine learning research in staffing & scheduling for healthcare professionals.
Liver fibrosis is a progressive pathological condition characterized by hepatic stellate cell (HSC) activation and vascular endothelial dysfunction, where single-target therapies often fail to disrupt the pathological feedback loop between inflammation and extracellular matrix (ECM) deposition. In this study, we developed a dual-targeted nanocarrier system functionalized with α-smooth muscle actin...
Ecosystems are rapidly degrading. Widely used approaches to monitor ecosystems to manage them effectively are both expensive and time consuming. The recent proliferation of publicly available imagery from satellites, Google Earth, and citizen-science platforms holds the promise to revolutionising ecological monitoring and optimising their efficiency. However, the potential of these platforms to de...
The rapid proliferation of digital pathology foundation models (FMs), spanning widely in architectural scales and pre-training datasets, poses a signi...
The rapid advancement of DNA foundation language models has brought about a transformative shift in genomics, allowing for the deciphering of intricat...
Antibodies play a central role in neutralizing pathogens through direct interference with viral entry and recruitment of effector immune cells. Howeve...
Immoral decisions, which engage both cognitive control and reward system, bring both cognitive and neural consequences. However, how dishonesty has an...
Robotic specimen processing is transforming biodiversity discovery by replacing labor-intensive handling with scalable systems that can simultaneously...
Theories of the neural mechanism underpinning rapid recognition debate whether it relies solely on a feedforward sweep through the ventral stream or i...
Understanding how the cortex encodes sensory input in a biologically efficient and computationally robust manner remains a central question in neurosc...
Despite the maturation of cryogenic electron microscopy (cryoEM) methodologies, generating high-resolution three-dimensional (3-D) reconstructions fro...
The rational design of high-specificity binders to peptide–HLA (pHLA) complexes remains a major challenge in personalized immunotherapy, particularly ...
Populations of neurons in motor cortex signal voluntary movement. Most classic neural encoding models and current brain-computer interface decoders as...
Advances in functional magnetic resonance imaging (fMRI) have led to the ability to study the brain across many contexts. However, the large number of...
This study presents a comprehensive, modular framework for AI-driven drug discovery (DD) and clinical trial simulation, spanning from target identific...
Major depressive disorder (MDD), bipolar disorder (BP), and schizophrenia (SCZ) involve learning impairments with poorly understood mechanisms. Unders...
Elasmobranchs (sharks, rays, and skates) face unprecedented extinction risk, with over one-third of species threatened primarily by overfishing. While...
Deep learning has notably advanced the field of liquid chromatography–mass spectrometry-based proteomics. Accurate prediction of peptide retention tim...
Potato leaf diseases pose a serious challenge to global food security, often leading to considerable yield losses if not detected promptly. The growin...
This study focused on the development of machine-learning- (ML) based strategies for mitigating nitrous oxide (N2O) emissions from various wastewater ...
Deep learning models are often characterized as black boxes because their layers of various mathematical transformations and activation functions are ...