0000000000294601

AUTHOR

Nadya Pyatigorskaya

showing 4 related works from this author

Automated classification of neurodegenerative parkinsonian syndromes using multimodal magnetic resonance imaging in a clinical setting

2020

ABSTRACTBackgroundSeveral studies have shown that machine learning algorithms using MRI data can accurately discriminate parkinsonian syndromes. Validation under clinical conditions is missing.ObjectivesTo evaluate the accuracy for the categorization of parkinsonian syndromes of a machine learning algorithm trained with a research cohort and tested on an independent clinical replication cohort.Methods361 subjects, including 94 healthy controls, 139 patients with PD, 60 with PSP with Richardson’s syndrome, 41 with MSA of the parkinsonian variant (MSA-P) and 27 with MSA of the cerebellar variant (MSA-P), were recruited. They were divided into a training cohort (n=179) scanned in a research en…

medicine.medical_specialtymedicine.diagnostic_testbusiness.industryParkinsonismMagnetic resonance imagingmedicine.diseaseTraining cohortnervous system diseases030218 nuclear medicine & medical imagingParkinsonian syndromes03 medical and health sciences0302 clinical medicinePhysical medicine and rehabilitationstomatognathic systemnervous systemCategorizationmental disordersReplication (statistics)Research environmentCohortmedicinebusiness030217 neurology & neurosurgery
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Automated Categorization of Parkinsonian Syndromes Using Magnetic Resonance Imaging in a Clinical Setting

2020

Background Machine learning algorithms using magnetic resonance imaging (MRI) data can accurately discriminate parkinsonian syndromes. Validation in patients recruited in routine clinical practice is missing. Objective The aim of this study was to assess the accuracy of a machine learning algorithm trained on a research cohort and tested on an independent clinical replication cohort for the categorization of parkinsonian syndromes. Methods Three hundred twenty-two subjects, including 94 healthy control subjects, 119 patients with Parkinson's disease (PD), 51 patients with progressive supranuclear palsy (PSP) with Richardson's syndrome, 35 with multiple system atrophy (MSA) of the parkinsoni…

0301 basic medicinemedicine.medical_specialtyParkinson's diseaseParkinson's diseasemultiple system atrophyProgressive supranuclear palsyDiagnosis Differential03 medical and health sciences0302 clinical medicinePhysical medicine and rehabilitationParkinsonian DisordersmedicineHumansmultimodal magnetic resonance imagingReceiver operating characteristicmedicine.diagnostic_testbusiness.industryParkinsonismMagnetic resonance imagingprogressive supranuclear palsymedicine.diseaseMagnetic Resonance Imaging3. Good healthnervous system diseasesmachine learning algorithm030104 developmental biologyDiffusion Tensor ImagingNeurologyCategorizationnervous systemCohort[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]Neurology (clinical)Supranuclear Palsy Progressivebusiness030217 neurology & neurosurgeryDiffusion MRI
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An International Survey of Quality and Safety Programs in Radiology

2021

Purpose: The aim of this study was to determine the status of radiology quality improvement programs in a variety of selected nations worldwide. Methods: A survey was developed by select members of the International Economics Committee of the American College of Radiology on quality programs and was distributed to committee members. Members responded on behalf of their country. The 51-question survey asked about 12 different quality initiatives which were grouped into 4 themes: departments, users, equipment, and outcomes. Respondents reported whether a designated type of quality initiative was used in their country and answered subsequent questions further characterizing it. Results: The re…

safetymedicine.medical_specialtyCanadaQuality managementAsiaInternationalitymedia_common.quotation_subjectquality improvementinternational surveymedicineHumansRadiology Nuclear Medicine and imagingQuality (business)value-addedSocieties Medicalmedia_commonQuality of Health Carebusiness.industryInternational surveyAustraliaGeneral MedicineglobalUnited StatesVariety (cybernetics)Europepeer-reviewHealth Care SurveysRadiologybusinessRadiologyProgram Evaluation
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Supplemental_material - An International Survey of Quality and Safety Programs in Radiology

2020

Supplemental_material for An International Survey of Quality and Safety Programs in Radiology by Jeremy Dick, Kathryn E. Darras, Frank J. Lexa, Erika Denton, Shigeru Ehara, Howard Galloway, Bhavin Jankharia, Pam Kassing, Kanako Kunishima Kumamaru, Peter Mildenberger, Sergey Morozov, Nadya Pyatigorskaya, Bin Song, Jacob Sosna, Marcus van Buchem and Bruce B. Forster in Canadian Association of Radiologists Journal

110320 Radiology and Organ ImagingFOS: Clinical medicine
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