TY - JOUR
T1 - “Big Data” in Rheumatology: Intelligent Data Modeling Improves the Quality of Imaging Data
AU - Landewé, Robert B. M.
AU - van der Heijde, D. sirée
PY - 2018
Y1 - 2018
N2 - Analysis of imaging data in rheumatology is a challenge. Reliability of scores is an issue for several reasons. Signal-to-noise ratio of most imaging techniques is rather unfavorable (too little signal in relation to too much noise). Optimal use of all available data may help to increase credibility of imaging data, but knowledge of complicated statistical methodology and the help of skilled statisticians are required. Clinicians should appreciate the merits of sophisticated data modeling and liaise with statisticians to increase the quality of imaging results, as proper imaging studies in rheumatology imply more than a supersensitive imaging technique alone.
AB - Analysis of imaging data in rheumatology is a challenge. Reliability of scores is an issue for several reasons. Signal-to-noise ratio of most imaging techniques is rather unfavorable (too little signal in relation to too much noise). Optimal use of all available data may help to increase credibility of imaging data, but knowledge of complicated statistical methodology and the help of skilled statisticians are required. Clinicians should appreciate the merits of sophisticated data modeling and liaise with statisticians to increase the quality of imaging results, as proper imaging studies in rheumatology imply more than a supersensitive imaging technique alone.
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85044712623&origin=inward
UR - https://www.ncbi.nlm.nih.gov/pubmed/29622297
U2 - https://doi.org/10.1016/j.rdc.2018.01.007
DO - https://doi.org/10.1016/j.rdc.2018.01.007
M3 - Review article
C2 - 29622297
SN - 0889-857X
VL - 44
SP - 307
EP - 315
JO - Rheumatic diseases clinics of North America
JF - Rheumatic diseases clinics of North America
IS - 2
ER -