Improving predictive models of glaucoma severity by incorporating quality indicators-Reference-Cited by-同舟云学术

Improving predictive models of glaucoma severity by incorporating quality indicators

Published:2014-02 Issue:2 Volume:60 Page:103-112
ISSN:0933-3657
Container-title:Artificial Intelligence in Medicine
language:en
Short-container-title:Artificial Intelligence in Medicine

Author:

Sacchi Lucia,Tucker Allan,Counsell Steve,Garway-Heath David,Swift Stephen

Funder

EPSRC

National Institute for Health Research (NIHR) Biomedical Research Centre based at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology

Publisher

Elsevier BV

Subject

Artificial Intelligence,Medicine (miscellaneous)

Reference46 articles.

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2. Crossing the quality chasm: a new health system for the 21st century;Institute of Medicine,2001

3. How to save costs by reducing unnecessary testing: lean thinking in clinical practice;Vegting;Eur J Intern Med,2012

4. An improved method to estimate frequency of false positive answers in computerized perimetry;Olsson;Acta Ophthalmol Scand,1997

5. Reliability of computerized perimetric threshold tests as assessed by reliability indices and threshold reproducibility in patients with suspect and manifest glaucoma;Bengtsson;Acta Ophthalmol Scand,2000

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1. Comparison of Structural and Functional Features in Primary Angle-Closure and Open-Angle Glaucomas;Journal of Glaucoma;2023-11-28

2. Predicting Cardiovascular Risk in Athletes: Resampling Improves Classification Performance;International Journal of Environmental Research and Public Health;2020-10-28

3. An efficient Bayesian network for differential diagnosis using experts' knowledge;International Journal of Intelligent Computing and Cybernetics;2020-03-09

4. An application of generalised simulated annealing towards the simultaneous modelling and clustering of glaucoma;Journal of Heuristics;2019-05-14