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Journal ArticleDOI

Sample size and optimal designs for reliability studies

TLDR
A functional approximation to earlier exact results is shown to have excellent agreement with the exact results and one can use it easily without intensive numerical computation.
Abstract
A method is developed to calculate the required number of subjects k in a reliability study, where reliability is measured using the intraclass correlation rho. The method is based on a functional approximation to earlier exact results. The approximation is shown to have excellent agreement with the exact results and one can use it easily without intensive numerical computation. Optimal design configurations are also discussed; for reliability values of about 40 per cent or higher, use of two or three observations per subject will minimize the total number of observations required.

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Journal ArticleDOI

Validation of a fully automated liver segmentation algorithm using multi-scale deep reinforcement learning and comparison versus manual segmentation

TL;DR: The results of this study demonstrate that AI-powered fully automated liver volumetric analyses can be done with excellent accuracy, reproducibility, robustness, speed and agreement with the manual segmentation.
Journal ArticleDOI

Quantifying the Rate of Ellipsoid Zone Loss in Stargardt Disease.

TL;DR: In this article, the ellipsoid zone (EZ) was used to track disease progression in Stardgardt disease (STGD) patients with genetically confirmed ABCA4 gene mutations.
Journal ArticleDOI

Development of a bedside pain assessment kit for the classification of patients with osteoarthritis.

TL;DR: Simple BSTK procedures, consolidated in a kit, reliably classified OA patients into subgroups based on sensory profile, suggesting that OA Patients differ in underlying pain mechanisms, which is needed to confirm these subgroups and determine their validity in predicting response to treatment.
Journal ArticleDOI

Testing measurement reliability in older populations: methods for informed discrimination in instrument selection and application.

TL;DR: Confidence intervals as measures of precision for reliability coefficients, regression modeling as supplements for such omnibus reliability statistics, and unreliability detection as a goal of reliability testing distinct from reliability inference are recommended.
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What is the optimal sample size for DA?

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