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Cohort profile: a collaborative multicentre study of retinal optical coherence tomography in 539 patients with neuromyelitis optica spectrum disorders (CROCTINO).

Svenja SpecoviusHanna G ZimmermannFrederike Cosima OertelClaudia ChienCharlotte BereuterLawrence J CookMarco Aurélio Lana PeixotoMariana Andrade FontenelleHo Jin KimJae-Won HyunSu-Kyung JungJacqueline PalaceAdriana Roca-FernandezAlejandro Rubio DiazMaria Isabel LeiteSrilakshmi M SharmaFereshte AshtariRahele KafiehAlireza DehghaniMohsen PouraziziLekha PanditAnitha DcunhaOrhan AktasMarius RingelsteinPhilipp AlbrechtEugene MayCaryl TongcoLetizia LeocaniMarco PisaMarta RadaelliElena H Martinez-LapiscinaHadas Stiebel-KalishMark HellmannItay LotanSasitorn SirithoJérôme de SezeThomas SengerJoachim HavlaRomain MarignierCaroline TiliketeAlvaro Cobo CalvoDenis Bernardi BichuettiIvan Maynart TavaresNasrin AsgariKerstin SoelbergAyse AltintasRengin YildirimUygur TanriverdiAnu JacobSaif HudaZoe RimlerAllyson ReidYang Mao-DraayerIbis Soto de CastilloMichael R YeamanTerry J SmithAlexander U BrandtFriedemann Paulnull null
Published in: BMJ open (2020)
We are pursuing several scientific projects based on the repository, such as analysing retinal layer thickness measurements, in this cohort in an attempt to identify differences between distinct disease phenotypes, demographics and ethnicities. The dataset will be available for further projects to interested, qualified parties, such as those using specialised image analysis or artificial intelligence applications.
Keyphrases
  • optical coherence tomography
  • artificial intelligence
  • quality improvement
  • diabetic retinopathy
  • machine learning
  • big data
  • deep learning
  • optic nerve