Results 241 to 250 of about 7,929,866 (305)
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To investigate the value of constructing models based on habitat radiomics and pathomics for predicting the risk of progression in high‐grade gliomas. Methods This study conducted a retrospective analysis of preoperative magnetic resonance (MR) images and pathological sections from 72 patients diagnosed with high‐grade gliomas (52 ...
Yuchen Zhu +14 more
wiley +1 more source
Traumatic Microhemorrhages Are Not Synonymous With Axonal Injury
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Diffuse axonal injury (DAI) is caused by acceleration‐deceleration forces during trauma that shear white matter tracts. Susceptibility‐weighted MRI (SWI) identifies microbleeds that are considered the radiologic hallmark of DAI and are used in clinical prognostication.
Karinn Sytsma +9 more
wiley +1 more source
Some of the next articles are maybe not open access.
Related searches:
Related searches:
Learning for CasADi: Data-driven Models in Numerical Optimization
Conference on Learning for Dynamics & Control, 2023While real-world problems are often challenging to analyze analytically, deep learning excels in modeling complex processes from data. Existing optimization frameworks like CasADi facilitate seamless usage of solvers but face challenges when integrating ...
Tim Salzmann +4 more
semanticscholar +1 more source
IEEE Congress on Evolutionary Computation, 2022
In this paper the adaptive differential evolution algorithm is presented, which includes a set of concepts, such as linear bias change in parameter adaptation, repetitive generation of points for bound constraint handling, as well as non-linear ...
V. Stanovov, S. Akhmedova, E. Semenkin
semanticscholar +1 more source
In this paper the adaptive differential evolution algorithm is presented, which includes a set of concepts, such as linear bias change in parameter adaptation, repetitive generation of points for bound constraint handling, as well as non-linear ...
V. Stanovov, S. Akhmedova, E. Semenkin
semanticscholar +1 more source
Applied Soft Computing, 2021
This paper develops a novel population-based evolutionary method called cooperation search algorithm (CSA) to address the complex global optimization problem.
Zhong-kai Feng, Wen-jing Niu, Shuai Liu
semanticscholar +1 more source
This paper develops a novel population-based evolutionary method called cooperation search algorithm (CSA) to address the complex global optimization problem.
Zhong-kai Feng, Wen-jing Niu, Shuai Liu
semanticscholar +1 more source
Duck swarm algorithm: theory, numerical optimization, and applications
Cluster Computing, 2021A swarm intelligence-based optimization algorithm, named Duck Swarm Algorithm (DSA), is proposed in this study, which is inspired by the searching for food sources and foraging behaviors of the duck swarm.
Mengjian Zhang, Guihua Wen
semanticscholar +1 more source
Learning-based elephant herding optimization algorithm for solving numerical optimization problems
Knowledge-Based Systems, 2020The elephant herding optimization (EHO) is a recent swarm intelligence algorithm. This algorithm simulates the clan updating and separation behavior of elephants. The EHO method has been successfully deployed in various fields.
Wei Li, Gai-ge Wang, A. Alavi
semanticscholar +1 more source
Knowledge-Based Systems, 2019
Differential Evolution (DE) variants have been proven to be excellent algorithms in tackling real-parameter single objective numerical optimization because they have secured the front ranks of these competitions for many years.
Zhenyu Meng, Jeng‐Shyang Pan, K. Tseng
semanticscholar +1 more source
Differential Evolution (DE) variants have been proven to be excellent algorithms in tackling real-parameter single objective numerical optimization because they have secured the front ranks of these competitions for many years.
Zhenyu Meng, Jeng‐Shyang Pan, K. Tseng
semanticscholar +1 more source
Novel mutation strategy for enhancing SHADE and LSHADE algorithms for global numerical optimization
Swarm and Evolutionary Computation, 2019Proposing new mutation strategies to improve the optimization performance of differential evolution (DE) is an important research study. Therefore, the main contribution of this paper goes in three directions: The first direction is introducing a less ...
A. W. Mohamed +2 more
semanticscholar +1 more source