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Showing 1765-1785 of 5,030 articles

Analysis and evaluation of handwriting in patients with Parkinson's disease using kinematic, geometrical, and non-linear features.

BACKGROUND AND OBJECTIVES: Parkinson's disease is a neurological disorder that affects the motor sys...

Mar 2019 PMID: 31046995

Computational modeling of neuromuscular response to swing-phase robotic knee extension assistance in cerebral palsy.

Predicting subject-specific responses to exoskeleton assistance may aid in maximizing functional gai...

Mar 2019 PMID: 30862380

Classifying Breast Cancer Subtypes Using Multiple Kernel Learning Based on Omics Data.

It is very significant to explore the intrinsic differences in breast cancer subtypes. These intrins...

Mar 2019 PMID: 30866472

Discovery of small molecule binders of human FSHR(TMD) with novel structural scaffolds by integrating structural bioinformatics and machine learning algorithms.

BACKGROUND: The activation of follicle stimulating hormone receptor (FSHR) by FSH and the consequent...

Mar 2019 PMID: 30897497

Feasibility of simple machine learning approaches to support detection of non-glaucomatous visual fields in future automated glaucoma clinics.

OBJECTIVES: To assess the performance of feed-forward back-propagation artificial neural networks (A...

Mar 2019 PMID: 30833668

Non-invasive machine learning estimation of effort differentiates sleep-disordered breathing pathology.

OBJECTIVE: Obstructive sleep-disordered breathing (SDB) events, unlike central events, are associate...

Feb 2019 PMID: 30736016

Network abnormalities among non-manifesting Parkinson disease related LRRK2 mutation carriers.

Non-manifesting carriers (NMC) of the G2019S mutation in the LRRK2 gene represent an "at risk" group...

Feb 2019 PMID: 30793410

NCBoost classifies pathogenic non-coding variants in Mendelian diseases through supervised learning on purifying selection signals in humans.

State-of-the-art methods assessing pathogenic non-coding variants have mostly been characterized on ...

Feb 2019 PMID: 30744685

Finite-time cluster synchronization for a class of fuzzy cellular neural networks via non-chattering quantized controllers.

This paper considers the finite-time cluster synchronization (FTCS) of coupled fuzzy cellular neural...

Feb 2019 PMID: 30785012

Predicting centre of mass horizontal speed in low to severe swimming intensities with linear and non-linear models.

We aimed to compare multilayer perceptron (MLP) neural networks, radial basis function neural networ...

Feb 2019 PMID: 30724700

Microbiological validation of a robot for the sterile compounding of injectable non-hazardous medications in a hospital environment.

OBJECTIVES: To design and execute a comprehensive microbiological validation protocol to assess a br...

Feb 2019 PMID: 32296508

The Effect of the Prethanol Extract of Trifolium pratense Leaves on Interleukin-1β-Induced Cartilage Matrix Degradation in Primary Rat Chondrocytes.

BACKGROUND: Osteoarthritis (OA) is a degenerative joint disease, characterized by cartilage degradat...

Jan 2019 PMID: 30703768

Machine learning vs addiction therapists: A pilot study predicting alcohol dependence treatment outcome from patient data in behavior therapy with adjunctive medication.

BACKGROUND AND OBJECTIVES: Clinical staff providing addiction treatment predict patient outcome poor...

Jan 2019 PMID: 30797388

What Machine Learning Can Tell Us About the Role of Language Dominance in the Diagnostic Accuracy of German LITMUS Non-word and Sentence Repetition Tasks.

The present study investigates the performance of 21 monolingual and 56 bilingual children aged 5;6-...

Jan 2019 PMID: 30761060

Endocrinology

Browse Categories

Analysis and evaluation of handwriting in patients with Parkinson's disease using kinematic, geometrical, and non-linear features.

Computational modeling of neuromuscular response to swing-phase robotic knee extension assistance in cerebral palsy.

Classifying Breast Cancer Subtypes Using Multiple Kernel Learning Based on Omics Data.

Discovery of small molecule binders of human FSHR(TMD) with novel structural scaffolds by integrating structural bioinformatics and machine learning algorithms.

Feasibility of simple machine learning approaches to support detection of non-glaucomatous visual fields in future automated glaucoma clinics.

Non-invasive machine learning estimation of effort differentiates sleep-disordered breathing pathology.

Network abnormalities among non-manifesting Parkinson disease related LRRK2 mutation carriers.

NCBoost classifies pathogenic non-coding variants in Mendelian diseases through supervised learning on purifying selection signals in humans.

Finite-time cluster synchronization for a class of fuzzy cellular neural networks via non-chattering quantized controllers.

Predicting centre of mass horizontal speed in low to severe swimming intensities with linear and non-linear models.

Microbiological validation of a robot for the sterile compounding of injectable non-hazardous medications in a hospital environment.

The Effect of the Prethanol Extract of Trifolium pratense Leaves on Interleukin-1β-Induced Cartilage Matrix Degradation in Primary Rat Chondrocytes.

Machine learning vs addiction therapists: A pilot study predicting alcohol dependence treatment outcome from patient data in behavior therapy with adjunctive medication.

What Machine Learning Can Tell Us About the Role of Language Dominance in the Diagnostic Accuracy of German LITMUS Non-word and Sentence Repetition Tasks.

Defining and discriminating responders from non-responders following transurethral resection of the prostate.

The Importance of G-protein Coupled Estrogen Receptor in Patients With Fibromyalgia.

Predicting radiation pneumonitis in locally advanced stage II-III non-small cell lung cancer using machine learning.

An active learning framework for enhancing identification of non-artifactual intracranial pressure waveforms.

Association Between Net Vertebral Artery Flow Volume and Non-AF Stroke: A Retrospective 2-Year Analysis.

Exercise-Associated Hyponatremia.

Machine learning models for predicting endocrine disruption potential of environmental chemicals.

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