Results 131 to 140 of about 15,644,966 (296)
Aging and Cancer, EarlyView.Cancer treatment is associated with measurable acceleration of biological aging across epigenetic, telomere, senescence, and immune biomarkers. However, biomarker validation and interventional strategies remain limited, especially in hematologic malignancies, underscoring the need for standardized multi‐omic aging assessments and adequately powered ...
Moataz Ellithi +3 more
wiley +1 more source
A K-means-like algorithm for informetric data clustering
, 2015 The K-means algorithm is one of the most often used clustering techniques. However, when it comes to discovering clusters in informetric data sets that consist of non-increasingly ordered vectors of not necessarily conforming lengths, such a method ...
Anna Cena (13497691) +1 more
core
, 2018 K-means clustering of differentially expressed genes changing over time (DEGots) from E6.5 to E17.5. The 5405 DEGots are clustered by K-means algorithm. n: number of genes in each cluster.
Joris A. van der Post (5775086) +5 more
core +1 more source
RNA Sequencing Resolves Cryptic Pathogenic Variants in Mitochondrial Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Mitochondrial diseases are the most common inherited metabolic disorders, characterized by pronounced clinical and genetic heterogeneity that complicates molecular diagnosis. Although DNA‐based sequencing approaches have become standard in genetic testing, up to half of patients remain without a definitive diagnosis.
Zhimei Liu +21 more
wiley +1 more source
Retracted: Blockchain and K-Means Algorithm for Edge AI Computing. [PDF]
Comput Intell Neurosci, 2023 Intelligence And Neuroscience C.
europepmc +1 more source
A Faster $k$-means++ Algorithm [PDF]
$k$-means++ is an important algorithm for choosing initial cluster centers for the $k$-means clustering algorithm. In this work, we present a new algorithm that can solve the $k$-means++ problem with nearly optimal running time. Given $n$ data points in $
Zhuo, Danyang +5 more
core
The 3 clusters with k-means algorithm.
, 2018 The 3 clusters with k-means algorithm.
Yuzhen Zhao (2743177) +2 more
core +1 more source
Predictive Ability of Plasma p‐tau217 for β‐Amyloid Status: A Prospective Multicenter Study
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Plasma tau phosphorylated at threonine 217 (p‐tau217) measured with fully automated platforms has shown high accuracy for Alzheimer's disease (AD) diagnosis, but real‐world multicenter data remain limited. We aimed to validate the diagnostic performance of p‐tau217 for identifying AD pathology in a real‐world multicenter cohort ...
Miquel Massons +33 more
wiley +1 more source
An Improved K-Means Algorithm Based on Contour Similarity
MathematicsThe traditional k-means algorithm is widely used in large-scale data clustering because of its easy implementation and efficient process, but it also suffers from the disadvantages of local optimality and poor robustness.
Jing Zhao +3 more
doaj +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Introduction Glucagon‐like peptide‐1 receptor agonists (GLP‐1 RAs) have demonstrated significant weight‐reducing effects and may offer benefits in idiopathic intracranial hypertension (IIH); however, recent concerns about the risk of non‐arteritic anterior ischemic optic neuropathy (NAION) have emerged.
Faisal A. Al‐Harbi +9 more
wiley +1 more source