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Multimodal, multitask, multiattention (M3) deep learning detection of reticular pseudodrusen: Toward automated and accessible classification of age-related macular degeneration.

Qingyu ChenTiarnan D L KeenanAlexis AllotYifan PengElvira AgrónAmitha DomalpallyCaroline C W KlaverDaniel T LuttikhuizenMarcus H ColyerCatherine A CukrasHenry E WileyM Teresa MagoneChantal Cousineau-KriegerWai T WongYingying ZhuEmily Y ChewZhiyong Lunull null
Published in: Journal of the American Medical Informatics Association : JAMIA (2021)
This study demonstrates the successful development, robust evaluation, and external validation of a novel deep learning framework that enables accessible, accurate, and automated AMD diagnosis and prognosis.
Keyphrases
  • deep learning
  • age related macular degeneration
  • artificial intelligence
  • convolutional neural network
  • machine learning
  • high resolution
  • high throughput
  • label free
  • real time pcr
  • chronic pain
  • quantum dots