Results 101 to 110 of about 589,029 (277)

Improved Selective Deep-Learning-Based Clustering Ensemble

Applied Sciences
Clustering ensemble integrates multiple base clustering results to improve the stability and robustness of the single clustering method. It consists of two principal steps: a generation step, which is about the creation of base clusterings, and a ...
Yue Qian, Shixin Yao, Tianjun Wu, You Huang, Lingbin Zeng   +4 more
doaj   +1 more source

Super‐Refractory Status Epilepticus (SRSE) in a Patient With Compound Heterozygous OPA1 Variants: Case Report and Literature Review

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Super‐Refractory Status Epilepticus (SRSE) is a rare, life‐threatening neurological emergency with unclear etiology in many cases. Mitochondrial dysfunction, often due to disease‐causing genetic variants, is increasingly recognized as a cause, with each gene producing distinct pathophysiological mechanisms.
Pouria Mohammadi, Lara Basovic, Christopher Michael McGraw   +2 more
wiley   +1 more source

Cluster validity indices for automatic clustering: A comprehensive review

Heliyon
The Cluster Validity Index is an integral part of clustering algorithms. It evaluates inter-cluster separation and intra-cluster cohesion of candidate clusters to determine the quality of potential solutions.
Abiodun M. Ikotun, Faustin Habyarimana, Absalom E. Ezugwu   +2 more
doaj   +1 more source

Two generalizations of Kohonen clustering [PDF]

The relationship between the sequential hard c-means (SHCM), learning vector quantization (LVQ), and fuzzy c-means (FCM) clustering algorithms is discussed. LVQ and SHCM suffer from several major problems.
Bezdek, James C., Pal, Nikhil R., Tsao, Eric C. K.   +2 more
core   +1 more source

Development of a Prediction Model for Progression Risk in High‐Grade Gliomas Based on Habitat Radiomics and Pathomics

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, Yuxi Gong, Weilin Xu, Xingjian Sun, Gefei Jiang, Lei Qiu, Kexin Shi, Mengxing Wu, Yinjiao Fei, Jinling Yuan, Jinyan Luo, Yurong Li, Yuandong Cao, Minhong Pan, Shu Zhou   +14 more
wiley   +1 more source

Towards Enhancement of Performance of K-Means Clustering Using Nature-Inspired Optimization Algorithms

The Scientific World Journal, 2014
Traditional K-means clustering algorithms have the drawback of getting stuck at local optima that depend on the random values of initial centroids. Optimization algorithms have their advantages in guiding iterative computation to search for global optima
Simon Fong, Suash Deb, Xin-She Yang, Yan Zhuang   +3 more
doaj   +1 more source

Unraveling the Molecular Mechanisms of Glioma Recurrence: A Study Integrating Single‐Cell and Spatial Transcriptomics

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Glioma recurrence severely impacts patient prognosis, with current treatments showing limited efficacy. Traditional methods struggle to analyze recurrence mechanisms due to challenges in assessing tumor heterogeneity, spatial dynamics, and gene networks.
Lei Qiu, Yinjiao Fei, Jiaxuan Ding, Kexin Shi, Jinyan Luo, Yuchen Zhu, Xingjian Sun, Gefei Jiang, Yuandong Cao, Weilin Xu, Shu Zhou   +10 more
wiley   +1 more source

Selection of suppliers using crisp gradual means integral in conjunction with clustering algorithms. [PDF]

MethodsX, 2023
Abdelhadi A, Almomani M.
europepmc   +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, Rhonda Mittenzwei, Heather Maioli, Amanda Kirkland, C. Dirk Keene, Ramon Diaz‐Arrastia, Christine Mac Donald, Chiara Maffei, Brian L. Edlow, Amber L. Nolan   +9 more
wiley   +1 more source

Selecting Clustering Algorithms for Identity-By-Descent Mapping. [PDF]

Pac Symp Biocomput, 2023
Shemirani R, Belbin GM, Burghardt K, Lerman K, Avery CL, Kenny EE, Gignoux CR, Ambite JL.   +7 more
europepmc   +1 more source