Clinical Decision Support for Automated OCT Imagery Interpretation
Principal Investigator: Dr Nicolas Jaccard
Approved Research ID: 30043
Approval date: April 6th 2018
The aim of this research is to quantitatively evaluate the agreement between Human experts and algorithms for the automated detection of pathologies in OCT imagery. The pathologies investigated include dry & wet age-related macular degeneration (AMD) and diabetic retinopathy. The proposed research aims at significantly improving screening capabilities for prevalent eye pathologies (e.g. age-related macular degeneration). As such, it will enable early detection of said pathologies, greatly improving patient outcome while minimising cost to the providers and healthcare system as a whole. The OCT imagery contained in the biobank uk dataset will be used to develop Artificial Intelligence (AI) algorithms for the detection of eye-related pathologies. This research relies on the availability of large and diverse datasets. Therefore, we would like to request all records of physical eye measurements (including OCT imagery) currently available in the biobank uk dataset.