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Quantification of Fundus Autofluorescence Features in a Molecularly Characterized Cohort of More Than 3000 Inherited Retinal Disease Patients from the United Kingdom.

William WoofThales Antonio Cabral de GuimaraesSaoud Al-KhuzaeiMalena Daich VarelaSagnik SenPallavi BaggaBernardo MendesMital ShahPaula BurkeDavid ParrySiying LinGunjan NaikBiraja GhoshalBart LiefersDun Jack FuMichalis GeorgiouQuang NguyenAlan Sousa da SilvaYichen LiuYu Fujinami-YokokawaNathaniel KabiriDayyanah SumodheePraveen J PatelJennifer FurmanIsmail MoghulJuliana Maria Ferraz SallumSamantha Roshani De SilvaBirgit LorenzFrank G HolzKaoru FujinamiAndrew R WebsterOmar A MahrooSusan M DownesSavita MadhusudhanKonstantinos BalaskasMichel MichaelidesNikolas Pontikos
Published in: medRxiv : the preprint server for health sciences (2024)
We have conducted the first large-scale cross-sectional and longitudinal quantitative analysis of FAF features across a diverse range of IRDs using a novel AI approach.
Keyphrases
  • cross sectional
  • end stage renal disease
  • diabetic retinopathy
  • ejection fraction
  • chronic kidney disease
  • newly diagnosed
  • prognostic factors
  • peritoneal dialysis
  • machine learning
  • mass spectrometry