Results 171 to 180 of about 155,766 (268)

Comparative Efficacy of Exercise Interventions for Anxiety Disorders: A Bayesian Network Meta-Analysis. [PDF]

Psychol Res Behav Manag
Liu J, Wang H, Lan Y, Yuan D, Du B, Zhou Y, Zhang W, Ke XW, Jiang Q, Wang F, Cao S, Sun J.   +11 more
europepmc   +1 more source

Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics

Advanced Intelligent Discovery, EarlyView.
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong, Zijian Huang, Xuanwu Wang, Zhenghui Feng, Wei Liu, Bingding Huang   +5 more
wiley   +1 more source

A bayesian network approach for systemic risk analysis in unmanned aerial vehicle (UAV) operations. [PDF]

Sci Rep
Wang L, Zhu M, Li N.
europepmc   +1 more source

Factorization Machine with Iterative Quantum Reverse Annealing: A Python Package for Batch Black‐Box Optimization With Reverse Quantum Annealing

Advanced Intelligent Discovery, EarlyView.
Factorization machine with iterative quantum reverse annealing (FMIRA) leverages quantum reverse annealing to perform batch black‐box optimization. Factorization machine with quantum annealing (FMQA) is a widely used python package for solving black‐box optimization problems using D‐Wave quantum annealers.
Andrejs Tučs, Ryo Tamura, Koji Tsuda
wiley   +1 more source

Probabilistic mapping of lymph node metastasis in epithelial ovarian cancer: a retrospective cohort study using Bayesian network analysis. [PDF]

Front Oncol
Xu H, Wu C, Chen Y, Wu L, Ling Q, Yang S, Lai H, Wen W, Tan H, Yao S, Sun T, Yang G.   +11 more
europepmc   +1 more source

Toward Intelligent Multimodal Holography for Real‐Time Chemical Imaging of Dynamic Ion Separation

Advanced Intelligent Discovery, EarlyView.
Intelligent multimodal holography integrates digital off‐axis holography, spectroscopic imaging, and AI‐driven reconstruction to visualize ion transport and chemical dynamics in real time. In this perspective paper, we outline how this approach enables label‐free, chemically specific monitoring of complex environments and discuss its potential to ...
Giovanna Ricchiuti, Sarah I. Allec, Maxim Ziatdinov, Venkateshkumar Prabhakaran   +3 more
wiley   +1 more source

Aerobic exercise versus acupuncture as adjuncts to acetylcholinesterase inhibitors in Alzheimer's disease: a systematic review and Bayesian network meta-analysis. [PDF]

Am J Clin Exp Immunol
Yu Z, Li H, Wang Y, Shen F, Wang Y.
europepmc   +1 more source

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

Advanced Intelligent Discovery, EarlyView.
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath, Shauryaraj K. Jilkar, Aditya Udgaonkar, Yu (Joe) Lu, Ali Mesbah   +4 more
wiley   +1 more source

BCTI: a Bayesian network-based method for revealing critical transitions in complex biological systems. [PDF]

PeerJ
Tong Y, Hong R, Yang N, Chen P, Peng H, Tang H, Liu R.   +6 more
europepmc   +1 more source

Modeling hierarchical relationships in epidemiological studies: a Bayesian networks approach

Hierarchical relationships between risk factors are seldom taken into account in epidemiological studies though some authors stressed the importance of doing so, and proposed a conceptual framework in which each level of the hierarchy is modeled ...
Nguefack-Tsague, Georges, Zucchini, Walter   +1 more
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