Clinical decision support system helps diagnose dry eye disease quickly
A system designed to help ophthalmologists diagnose dry eye disease more quickly appears to be accurate, according to a new study.
In the first phase of research, 37 cornea specialists identified what they considered the most important diagnostic parameters. In the second phase, a clinical decision support system was designed and implemented by using MATLAB software. Patient data (n = 50) was collected from a teaching hospital and used to evaluate the system.
Diagnostic parameters for dry eye disease included:
-Meibomian gland dysfunction
-Score of ocular surface disease index
-Schirmer’s test result
-Tear meniscus height
-Tear breakup time
-Fluorescein staining score
The system output variables were the diagnosis and severity of dry eye disease at four levels for the right and left eyes, separately.
The accuracy of the system was shown to be 96.9%, sensitivity at 97.5%, and specificity at 93.7%.
Ebrahimi F, Ayatollahi H, Aghaei H. A clinical decision support system for diagnosing and determining severity of dry eye disease. Eye (Lond). 2022;doi: 10.1038/s41433-022-02197-x. Epub ahead of print. PMID: 35996022.
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