Results 41 to 50 of about 606,186 (241)

Classification of Cardiovascular Disease Gene Data Using Discriminant Analysis and Support Vector Machine (SVM)

open access: yesBerkala Sainstek, 2022
Cardiovascular disease is a disease caused by impaired function of the heart and blood vessels. This disease is caused by many factors, one of which is genetics, while the causes are age, gender, and family history.
Rizky Prayogo   +2 more
doaj   +1 more source

Optimasi Kernel K-Means dalam Pengelompokan Kabupaten/Kota Berdasarkan Indeks Pembangunan Manusia di Indonesia [PDF]

open access: yes, 2018
Kernel k-means (KKC) bekerja dengan mengubah data dari initial space ke dalam featured space dan k-means dijalankan menggunakan data featured space tersebut.
Aprianto, K. (Kasiful)
core  

Unified Spectral Clustering with Optimal Graph

open access: yes, 2017
Spectral clustering has found extensive use in many areas. Most traditional spectral clustering algorithms work in three separate steps: similarity graph construction; continuous labels learning; discretizing the learned labels by k-means clustering ...
Cheng, Qiang   +3 more
core   +1 more source

Fluid Biomarkers of Disease Burden and Cognitive Dysfunction in Progressive Supranuclear Palsy

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Identifying objective biomarkers for progressive supranuclear palsy (PSP) is crucial to improving diagnosis and establishing clinical trial and treatment endpoints. This study evaluated fluid biomarkers in PSP versus controls and their associations with regional 18F‐PI‐2620 tau‐PET, clinical, and cognitive outcomes.
Roxane Dilcher   +10 more
wiley   +1 more source

Identifying and evaluating clinical subtypes of Alzheimer’s disease in care electronic health records using unsupervised machine learning

open access: yesBMC Medical Informatics and Decision Making, 2021
Background Alzheimer’s disease (AD) is a highly heterogeneous disease with diverse trajectories and outcomes observed in clinical populations. Understanding this heterogeneity can enable better treatment, prognosis and disease management. Studies to date
Nonie Alexander   +3 more
doaj   +1 more source

Nyström method with Kernel K-means++ samples as landmarks [PDF]

open access: yes, 2017
We investigate, theoretically and empirically, the effectiveness of kernel K-means++ samples as landmarks in the Nyström method for low-rank approximation of kernel matrices. Previous empirical studies (Zhang et al., 2008; Kumar et al.,2012) observe that
Gaertner, Thomas, Oglic, Dino
core  

Multivariate transient price impact and matrix-valued positive definite functions

open access: yes, 2015
We consider a model for linear transient price impact for multiple assets that takes cross-asset impact into account. Our main goal is to single out properties that need to be imposed on the decay kernel so that the model admits well-behaved optimal ...
Alfonsi, Aurélien   +2 more
core   +3 more sources

Relationship Between Neurologic Symptoms and Signs and FMR1 Genotype in Premutation Carriers

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background and Objectives Fragile X‐associated Tremor/Ataxia Syndrome (FXTAS) is the most severe late‐onset condition caused by a premutation in the FMR1 gene, characterized by expanded CGG triplet repeats of 55–200. Clinical presentations of FXTAS, including gait ataxia, kinetic tremor, cognitive decline, and rare Parkinsonism, are linked to ...
Flora Tassone   +8 more
wiley   +1 more source

Differentially Private Mixture of Generative Neural Networks [PDF]

open access: yes, 2017
Generative models are used in a wide range of applications building on large amounts of contextually rich information. Due to possible privacy violations of the individuals whose data is used to train these models, however, publishing or sharing ...
Acs, Gergely   +3 more
core   +5 more sources

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

open access: yesAdvanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt   +8 more
wiley   +1 more source

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