0000000000294601
AUTHOR
Nadya Pyatigorskaya
Automated classification of neurodegenerative parkinsonian syndromes using multimodal magnetic resonance imaging in a clinical setting
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…
Automated Categorization of Parkinsonian Syndromes Using Magnetic Resonance Imaging in a Clinical Setting
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…
Supplemental_material - An International Survey of Quality and Safety Programs in Radiology
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
An International Survey of Quality and Safety Programs in Radiology
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…