Results 241 to 250 of about 173,528,053 (291)

Clinical Validation of Artificial Intelligence (AI)‐based Cartilage Segmentation Predicting Knee Replacement

open access: yesArthritis Care &Research, Accepted Article.
Objective For cartilage morphology to serve as a scalable endpoint in clinical trials, analyses should be performed automatically without human interaction. To clinically validate artificial intelligence (AI)‐based analysis, we studied cartilage loss from MRI prior to knee replacement.
Felix Eckstein   +3 more
wiley   +1 more source

Validation of Patient‐Reported Outcomes Measurement Information System (PROMIS) Pediatric Measures for Children With Chronic Nonbacterial Osteomyelitis

open access: yesArthritis Care &Research, EarlyView.
Objective To assess the validity of the Patient‐Reported Outcomes Measurement Information System (PROMIS) Pediatric measures in patients with chronic nonbacterial osteomyelitis (CNO). Methods Within the longitudinal patient registry of CNO, English‐speaking patients aged 8 years and older self‐reported PROMIS Pediatric measures of fatigue, pain ...
Mary M. Eckert   +43 more
wiley   +1 more source

Automated Hand Flexor Tendon–Thickness Measurement in Systemic Sclerosis

open access: yesArthritis Care &Research, EarlyView.
Objective Systemic sclerosis (SSc) can affect flexor tendons, contributing to hand function problems and reduced quality of life. Tendon changes are currently assessed with ultrasonography and measured manually, a time‐consuming process prone to interobserver variability.
Mark Greveling   +4 more
wiley   +1 more source

Microvascular Damage Is Associated With Carotid Wall Structural Changes in Systemic Sclerosis: A Capillaroscopy and Ultrasound‐Based Observational Study

open access: yesArthritis Care &Research, EarlyView.
Objective Systemic sclerosis (SSc) is characterized by cardiovascular risk excess not fully explained by traditional factors. Whether the severity of microvascular damage correlates with structural subclinical atherosclerosis remains unclear. We investigated the relationship between nailfold videocapillaroscopy (NVC) abnormalities and carotid ...
Eugenio Capparelli   +13 more
wiley   +1 more source

Survival Outcomes in Older Adults With Axial Spondyloarthritis and Concomitant Cancer

open access: yesArthritis Care &Research, EarlyView.
Objective The objective of this study was to determine survival outcomes in older adults with axial spondyloarthritis (axSpA) and concomitant cancer. Methods We conducted a population‐based study using Medicare claims data linked to Surveillance, Epidemiology, and End Results data to determine overall survival (OS) and cancer‐specific survival (CSS) in
Savannah Bowman   +7 more
wiley   +1 more source

Development of Patient‐Reported Outcome Measures for Early Systemic Sclerosis Across Disease Subtypes

open access: yesArthritis Care &Research, Accepted Article.
Objective Existing patient‐reported outcome (PRO) measures for systemic sclerosis (SSc) have important limitations, including inadequate coverage of early disease and limited inclusion of diffuse cutaneous (dcSSc) and limited cutaneous (lcSSc) subtypes.
George J. Greene   +5 more
wiley   +1 more source

Goodness-of-Fit

open access: yes, 2022
Goodness-of-fit.
Gábor J. Székely, Maria L. Rizzo
core   +3 more sources

Goodness of Fit

IEEE Software, 2006
It appears to be with software architectures: for a given domain, even across the decades, forces are at play that are best resolved by a common architectural pattern that allows variants. One architectural style might be deemed "better" than another for that domain because it better resolves those forces. In that sense, there's a goodness of fit - not
Fred Campano, Dominick Salvatore
  +5 more sources

Fitting In and Doing Good, or Doing Good to Fit In?

Academy of Management Proceedings, 2023
Fitting In and Doing Good, or Doing Good to Fit In?
Wouter Vleugels, Huw Flatau Harrison
openaire   +1 more source

Smooth Tests of Goodness of Fit

Technometrics, 1991
AbstractSmooth tests of goodness of fit assess the fit of data to a given probability density function within a class of alternatives that differs ‘smoothly’ from the null model. These alternatives are characterized by their order: the greater the order the richer the class of alternatives. The order may be a specified constant, but data‐driven methods
Rayner, J. C. W., Thas, O., Best, D. J.
openaire   +2 more sources

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