Results 151 to 160 of about 293,870 (330)

Clean Cut (adaptive, multimodal surgical infection prevention programme) for low‐resource settings: a prospective quality improvement study

BJS (British Journal of Surgery), EarlyView., 2020
Clean Cut is a multimodal, adaptive, checklist‐based infection prevention programme designed to improve compliance with six critical perioperative infection prevention practices. After introducing the programme at five hospitals in Ethiopia, compliance with critical infection prevention standards significantly improved and the relative risk of ...
J. A. Forrester, N. Starr, T. Negussie, D. Schaps, M. Adem, S. Alemu, D. Amenu, N. Gebeyehu, T. Habteyohannes, F. Jiru, A. Tesfaye, E. Wayessa, R. Chen, A. Trickey, S. Bitew, A. Bekele, T. G. Weiser   +16 more
wiley   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

A Priori Ratemaking Using Bivariate Poisson Regression Models

, 2008
Lluı́s Bermúdez
openalex   +1 more source

Privacy-protecting estimation of adjusted risk ratios using modified Poisson regression in multi-center studies [PDF]

, 2019
Di Shu, Jessica G. Young, Sengwee Toh
openalex   +1 more source

Inverse Design of Alloys via Generative Algorithms: Optimization and Diffusion within Learned Latent Space

Advanced Intelligent Discovery, EarlyView.
This work presents a novel generative artificial intelligence (AI) framework for inverse alloy design through operations (optimization and diffusion) within learned compact latent space from variational autoencoder (VAE). The proposed work addresses challenges of limited data, nonuniqueness solutions, and high‐dimensional spaces.
Mohammad Abu‐Mualla, Ellis Crabtree, Fredrick Michael, Yayue Pan, Jida Huang   +4 more
wiley   +1 more source

Adjusting for Berkson error in exposure in ordinary and conditional logistic regression and in Poisson regression. [PDF]

BMC Med Res Methodol, 2023
Oraby T, Chakraborty S, Sivaganesan S, Kincl L, Richardson L, McBride M, Siemiatycki J, Cardis E, Krewski D.   +8 more
europepmc   +1 more source

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

Bayesian semi-parametric analysis of Poisson change-point regression models: application to policy-making in Cali, Colombia

, 2012
Taeyoung Park, Robert T. Krafty, Á. Sánchez   +2 more
openalex   +2 more sources

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

Parametric and non-parametric Poisson regression for modelling of the arterial input function in positron emission tomography. [PDF]

EJNMMI Phys, 2023
Matheson GJ, Ge L, Zhang M, Sun B, Tu Y, Zanderigo F, Forsberg Morèn A, Ogden RT.   +7 more
europepmc   +1 more source