A Crowdsourcing Approach to Develop Machine Learning Models to Quantify Radiographic Joint Damage in...
A Crowdsourcing Approach to Develop Machine Learning Models to Quantify Radiographic Joint Damage in Rheumatoid Arthritis
About this item
Full title
Author / Creator
RA2-DREAM Challenge Community , Sun, Dongmei , Nguyen, Thanh M , Allaway, Robert J , Wang, Jelai , Chung, Verena , Yu, Thomas V , Mason, Michael , Dimitrovsky, Isaac , Ericson, Lars , Li, Hongyang , Guan, Yuanfang , Israel, Ariel , Olar, Alex , Pataki, Balint Armin , Stolovitzky, Gustavo , Guinney, Justin , Gulko, Percio S , Frazier, Mason B , Chen, Jake Y , Costello, James C and Bridges, Jr, S Louis
Publisher
United States: American Medical Association
Journal title
Language
English
Formats
Publication information
Publisher
United States: American Medical Association
Subjects
More information
Scope and Contents
Contents
An automated, accurate method is needed for unbiased assessment quantifying accrual of joint space narrowing and erosions on radiographic images of the hands and wrists, and feet for clinical trials, monitoring of joint damage over time, assisting rheumatologists with treatment decisions. Such a method has the potential to be directly integrated in...
Alternative Titles
Full title
A Crowdsourcing Approach to Develop Machine Learning Models to Quantify Radiographic Joint Damage in Rheumatoid Arthritis
Authors, Artists and Contributors
Author / Creator
Sun, Dongmei
Nguyen, Thanh M
Allaway, Robert J
Wang, Jelai
Chung, Verena
Yu, Thomas V
Mason, Michael
Dimitrovsky, Isaac
Ericson, Lars
Li, Hongyang
Guan, Yuanfang
Israel, Ariel
Olar, Alex
Pataki, Balint Armin
Stolovitzky, Gustavo
Guinney, Justin
Gulko, Percio S
Frazier, Mason B
Chen, Jake Y
Costello, James C
Bridges, Jr, S Louis
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9425151
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9425151
Other Identifiers
ISSN
2574-3805
E-ISSN
2574-3805
DOI
10.1001/jamanetworkopen.2022.27423
