Results 131 to 140 of about 586,435 (341)
Recognition of Disease in Leaves Using Genetic Algorithm and Neural Network Based Feature Selection
, 2023 D Angayarkanni, L. Jayasimman
openalex +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Facioscapulohumeral muscular dystrophy type 1 (FSHD1) is a progressive neuromuscular disorder with no approved treatments. Identifying reliable biomarkers is critical to monitor disease severity, activity, and progression. Interleukin‐6 (IL‐6) has been proposed as a candidate biomarker, but longitudinal validation is limited ...
Jonathan Pini +13 more
wiley +1 more source
The effect of feature selection using genetic algorithms on spectral-spatial classification of hyperspectral imagery [PDF]
, 2015 Davood Akbari +2 more
openalex +1 more source
Diffusion Tractography Biomarker for Epilepsy Severity in Children With Drug‐Resistant Epilepsy
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To develop a novel deep‐learning model of clinical DWI tractography that can accurately predict the general assessment of epilepsy severity (GASE) in pediatric drug‐resistant epilepsy (DRE) and test if it can screen diverse neurocognitive impairments identified through neuropsychological assessments.
Jeong‐Won Jeong +7 more
wiley +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background There is growing recognition of the potential of plasma proteomics for Alzheimer's Disease (AD) risk assessment and disease characterization. However, differences between proteomics platforms introduce uncertainties regarding cross‐platform applicability.
Manyue Hu +9 more
wiley +1 more source
An investigation of messy genetic algorithms [PDF]
Genetic algorithms (GAs) are search procedures based on the mechanics of natural selection and natural genetics. They combine the use of string codings or artificial chromosomes and populations with the selective and juxtapositional power of reproduction
Deb, Kalyanmoy +2 more
core +1 more source
Copy Number Variants and Their Association With Intracerebral Hemorrhage Risk: A Case–Control Study
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Introduction Intracerebral Hemorrhage (ICH) is a leading cause of morbidity and mortality worldwide and lacks effective therapeutic interventions. Despite previous studies, the genetic underpinnings of ICH remain poorly understood. We sought to investigate the role of copy number variants (CNVs) in ICH pathophysiology to identify novel ...
Savvina Prapiadou +12 more
wiley +1 more source