Results 161 to 170 of about 520,634 (314)

Integrating Surveillance and Stakeholder Insights to Predict Influenza Epidemics: A Bayesian Network Study in Queensland, Australia. [PDF]

Int J Environ Res Public Health
Sahin O, Phung H, Standke A, Rajmokan M, Raulli A, York A, Lee P.   +6 more
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

Integrative Bayesian Network Analysis of Genomic Data

Cancer Informatics, 2014
Yang Ni, Francesco C. Stingo, Veerabhadran Baladandayuthapani   +2 more
doaj  

Using data-driven Bayesian networks to analyze maritime accidents in congested waters

Takuya SAMESHIMA
openalex   +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

Immunotherapies in neuromyelitis optica: Bayesian network meta-analysis. [PDF]

J Neurol
John N, Lim A, Sunthar SR, Zhang L, Cheng J, Boktor J, Chong V, Ma H, Phan TG.   +8 more
europepmc   +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

Advanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa Ryu   +3 more
wiley   +1 more source

Vitamin D Receptor Gene Polymorphisms Differentiated Between Tuberculosis Disease and Infection: Causal Association Study

Infection and Drug Resistance
Jaina Razbek,1 Yanggui Chen,2 Jiandong Yang,2 Yaying Zhang,1 Baofeng Wen,1 Junan Wang,1 Xiaomin Wang,1 Guliziba Kuerbanjiang,1 Abulikemu Aili,1 Mingqin Cao1 1Department of Epidemiology and Health Statistics, College of Public Health, Xinjiang Medical ...
Razbek J, Chen Y, Yang J, Zhang Y, Wen B, Wang J, Wang X, Kuerbanjiang G, Aili A, Cao M   +9 more
doaj  

Development of a Bayesian Network and Information Gain-Based Axis Dynamic Mechanism for Ankle Joint Rehabilitation. [PDF]

Biomimetics (Basel)
Ma H, Bao Y, Lan J, Zhu X, Wan P, Cedazo León R, Jiang S, Chen F, Kang J, Guo Q, Zhang P, Li H.   +11 more
europepmc   +1 more source

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

Advanced Intelligent Discovery, EarlyView.
This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley   +1 more source