Results 211 to 220 of about 39,041 (304)
A machine learning framework simultaneously predicts four critical properties of monomers for emulsion polymerization: propagation rate constant, reactivity ratios, glass transition temperature, and water solubility. These tools can be used to systematically identify viable bio‐based monomer pairs as replacements for conventional formulations, with ...
Kiarash Farajzadehahary +1 more
wiley +1 more source
Reliability assessment of key equipment for coal gasification using artificial intelligence technology. [PDF]
Wu L, Zhang Z, Ding R, Zhang W, Liu M.
europepmc +1 more source
AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley +1 more source
Enhancing the pricing efficiency of financial assets with an optimized bayesian network based on efficient fusion. [PDF]
Fu Q, Li X.
europepmc +1 more source
Heterogeneous continuous dynamic Bayesian networks with flexible structure and inter-time segment information sharing [PDF]
Dondelinger, F., Husmeier, D., Lebre, S.
core
Uncertainty‐Guided Selective Adaptation Enables Cross‐Platform Predictive Fluorescence Microscopy
Deep learning models often fail when transferred to new microscopes. A novel framework overcomes this by selectively adapting the early layers governing low‐level image statistics, while freezing deep layers that encode morphology. This uncertainty‐guided approach enables robust, label‐free virtual staining across diverse systems, democratizing ...
Kai‐Wen K. Yang +9 more
wiley +1 more source
Likelihoods and posteriors of instrumental variable regression models with strongendogeneity and/or weak instruments may exhibit rather non-elliptical contours inthe parameter space.
Hoogerheide, L.F. +2 more
core
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi +2 more
wiley +1 more source
Multiscale parcellation of dynamic causal models of the brain. [PDF]
Zarghami TS.
europepmc +1 more source

