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2025

AI explainability in oculomics:

How it works, its role in establishing trust, and what still needs to be addressed.

2024

Retinal BioAge reveals indicators

of cardiovascular -kidney-metabolic syndrome in US and UK populations.

Blood Pressure Predicted

from Artificial Intelligence Analysis of Retinal Images Correlates with Future Cardiovascular Events.

Validation of neuron activation patterns

for artificial intelligence models in oculomics.

Association of retinal image-based, deep learning cardiac BioAge

with telomere length and cardiovascular biomarkers.

Development and validation of a deep-learning model

to predict 10-year ASCVD risk from retinal images using the UK Biobank and EyePACS 10K datasets.

2023

Examination of alternative eGFR definitions on the performance of deep learning models

for detection of chronic kidney disease from fundus photographs.

A multi-centre prospective evaluation of THEIA™

to detect diabetic retinopathy (DR) and diabetic macular oedema (DMO) in the New Zealand screening program.

Automation of Macular Degeneration Classification in the AREDS Dataset

Using a novel neural network design.

2022

Patients Perceptions of Artificial Intelligence in Diabetic Eye Screening.

Artificial intelligence (AI) technology is poised to revolutionize modern delivery of healthcare services.

2021

Prospective Study

THEIA™ development, and testing of artificial intelligence-based primary triage of diabetic retinopathy screening images in New Zealand.

2020

THEIA’s Performance
Assessed using a cloud platform

Towards implementation of AI in New Zealand national diabetic screening program: Cloud-based, robust, and bespoke.

Essentials of a Robust Deep Learning System

for Diabetic Retinopathy Screening: A Systematic Literature Review.

THEIA used OCTA for diagnosis of AMD

Quantification of Optical Coherence Tomography Angiography in Age and Age-Related Macular Degeneration Using Vessel Density Analysis.

THEIA as multi-modal imaging detection of AMD

Multimodal Retinal Image Analysis via Deep Learning for the Diagnosis of Intermediate Dry Age-Related Macular Degeneration: A Feasibility Study.

2019

THEIA as a smoking detection tool

Detection of smoking status from retinal images; a Convolutional Neural Network study.

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