Enhancing the pricing efficiency of financial assets with an optimized bayesian network based on efficient fusion. [PDF]
PLoS OneFu Q, Li X.
europepmc +1 more source
Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation
Advanced Intelligent Discovery, EarlyView.We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley +1 more source
Identifying contributing-factor configurations in reported bed falls: a Bayesian network-based exploratory study. [PDF]
Front Public HealthWang M +7 more
europepmc +1 more source
Bayesian and information-theoretic tools for neuroscience
, 2006 The overarching purpose of the studies presented in this report is the exploration of the uses of information theory and Bayesian inference applied to neural codes. Two approaches were taken: Starting from first principles, a coding mechanism is proposed,
Dominik M. Endres, Endres, Dominik M.
core
Deep Learning‐Assisted Design of Mechanical Metamaterials
Advanced Intelligent Discovery, EarlyView.This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
Comparative Safety of Intravenous Sedatives for Bronchoscopy: A Bayesian Network Meta-Analysis. [PDF]
Yonsei Med JLee J, Song JU.
europepmc +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Advanced Intelligent Discovery, EarlyView.Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
, 2008 Bayesian networks are a type of causal network used for probabilistic reasoning, which have found wide application in biomedical environments and machine vision.We have considered their application in the realm of security, where behaviour that is ...
Pickering, Jonathan, Xu, Zhijie
core
Advanced Experiment Design Strategies for Drug Development
Advanced Intelligent Discovery, EarlyView.Wang et al. analyze 592 drug development studies published between 2020 and 2024 that applied design of experiments methodologies. The review surveys both classical and emerging approaches—including Bayesian optimization and active learning—and identifies a critical gap between advanced experimental strategies and their practical adoption in ...
Fanjin Wang +3 more
wiley +1 more source
Risk assessment for canine periodontal disease using a hybrid causal Bayesian network. [PDF]
Front Vet SciO'Flynn C +8 more
europepmc +1 more source