Results 201 to 210 of about 997,820 (281)

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, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source

Exploring interrelationships between cognition, functioning and quality of life in schizophrenia spectrum disorders: a Bayesian analysis of networks. [PDF]

Eur Arch Psychiatry Clin Neurosci
Bastelica T, Huth K, Marsman M, Lespine LF, Barbalat G, Plasse J, Chéreau-Boudet I, Gouache B, Legros-Lafarge E, Massoubre C, Guillard-Bouhet N, Haesebaert F, d'Amato T, Franck N, Rey R.   +14 more
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, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source

Impact of violence on emotional exhaustion risk of registered nurses in Germany: a Bayesian analysis of cross-Sectional data with multiple imputations. [PDF]

BMC Nurs
Campione A, Henschke C.
europepmc   +1 more source

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, Anthony Harker, Mohan Edirisinghe, Maryam Parhizkar   +3 more
wiley   +1 more source

Identifying the relative contributions of body size across life course to midlife and late-life cognitive function: a Bayesian analysis from the Guangzhou Biobank Cohort Study. [PDF]

J Nutr Health Aging
Hou S, Wang J, Lam TH, Cheng KK, Zhang WS, Xu L.   +5 more
europepmc   +1 more source

Bayesian Analysis for Population Ecology [PDF]

Joseph Hilbe
core   +1 more source

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

Advanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas, Panagiotis Krokidas, Vasileios Vavourakis, Clara Essmann, George Giannakopoulos   +4 more
wiley   +1 more source

Bayesian analysis of non-communicable diseases risk factors: a focus on the lower-educated population in Bangladesh. [PDF]

Int Health
Hossain MI, Gupta MD, Ohi TF, Rahman MM.
europepmc   +1 more source