Autoencoder-based phenotyping of ophthalmic images highlights genetic loci influencing retinal morphology and provides epidemiologically informative biomarkers.
Panagiotis I. Sergouniotis, Adam Diakite, Kumar Gaurav, Naomi Allen, Tariq Mehmood Aslam, Denize Atan, Sarah Ann Barman, Jenny Barrett, Paul Bishop, Graeme Charles M. Black, Tasanee Braithwaite, Roxana Carare, Usha Chakravarthy, Michelle P. Y. Chan, Sharon Y. L. Chua, , Tomas Fitzgerald
The paper uses an autoencoder to derive retinal phenotypes from OCT images, identifies 118 genetic loci, and shows their relevance to retinal morphology and disease prediction.
Bioinformatics · Dec 5, 2024Peer-reviewedGenetic & Genomic Medicine