Symptom-based stratification algorithm for heterogeneous symptoms of dry eye disease: a feasibility study.

Ken Nagino Takenori InomataMasahiro NakamuraJaemyoung SungAkie Midorikawa-InomataMasao IwagamiKenta FujioYasutsugu AkasakiYuichi OkumuraTianxiang HuangKeiichi FujimotoAtsuko EguchiMaria MiuraShokirova HurramhonJun ZhuMizu OhnoKunihiko HirosawaYuki MorookaReza Dana Akira MurakamiHiroyuki Kobayashi

Published in: Eye (London, England) (2023)

The patients with DED who visited ophthalmologists were successfully stratified by the previously established algorithm for the general population, uncovering patterns for their seemingly heterogeneous and variable clinical characteristics of DED. The results have important implications for promoting treatment interventions tailored to individual patients and implementing smartphone-based clinical data collection in the future.

Keyphrases

end stage renal disease
machine learning
ejection fraction
deep learning
newly diagnosed
chronic kidney disease
physical activity
prognostic factors
quality improvement
smoking cessation
neural network
patient reported outcomes
electronic health record