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Jiri Fajtl

Showing results (1-10 of 10) with videos related to

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IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society|May 7, 2019
Improving Dataset Volumes and Model Accuracy with Semi-Supervised Iterative Self-LearningRobert Dupre, Jiri Fajtl, Vasileios Argyriou, et al.
Diabetologia|March 12, 2025
A simple score-based strategy to improve equity of the UK biennial diabetic eye screening protocol among people deemed as low riskMatilda Pitt, Abraham Olvera-Barrios, John Anderson, et al.
BMJ Open|November 15, 2023
What are the perceptions and concerns of people living with diabetes and National Health Service staff around the potential implementation of AI-assisted screening for diabetic eye disease? Development and validation of a survey for use in a secondary care screening settingKathryn Willis, Umar A R Chaudhry, Lakshmi Chandrasekaran, et al.
Diabetes Care|June 10, 2026
Head-to-Head Comparative Evaluation of Four Commercially Available Artificial Intelligence Systems for Detecting Referable Diabetic Retinopathy in a Tanzanian PopulationCharles R Cleland, Covadonga Bascaran, William U Makupa, et al.
The Lancet. Digital Health|November 25, 2025
Automated retinal image analysis systems to triage for grading of diabetic retinopathy: a large-scale, open-label, national screening programme in EnglandAlicja R Rudnicka, Royce Shakespeare, Ryan Chambers, et al.
The Lancet. Digital Health|April 4, 2025
Generating evidence to support the role of AI in diabetic eye screening: considerations from the UK National Screening CommitteeTrystan Macdonald, Zhivko Zhelev, Xiaoxuan Liu, et al.
Diabetes Research and Clinical Practice|December 21, 2024
Patient and practitioner perceptions around use of artificial intelligence within the English NHS diabetic eye screening programmeCharlotte Wahlich, Lakshmi Chandrasekaran, Umar A R Chaudhry, et al.
Diabetic Medicine : a Journal of the British Diabetic Association|November 10, 2025
What are the perceptions and concerns of people living with diabetes and National Health Service staff around the potential implementation of AI-assisted screening for diabetic eye disease?Kathryn Willis, Royce Shakespeare, Lakshmi Chandrasekaran, et al.
The British Journal of Ophthalmology|October 24, 2023
Two-year recall for people with no diabetic retinopathy: a multi-ethnic population-based retrospective cohort study using real-world data to quantify the effectAbraham Olvera-Barrios, Alicja R Rudnicka, John Anderson, et al.
BMJ Open Diabetes Research & Care|November 10, 2023
Ethnic disparities in progression rates for sight-threatening diabetic retinopathy in diabetic eye screening: a population-based retrospective cohort studyAbraham Olvera-Barrios, Christopher G Owen, John Anderson, et al.
Pageof 1

Showing results (1-10 of 10) with videos related to

Sort By:
Pageof 1
IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society|May 7, 2019
Improving Dataset Volumes and Model Accuracy with Semi-Supervised Iterative Self-LearningRobert Dupre, Jiri Fajtl, Vasileios Argyriou, et al.
Diabetologia|March 12, 2025
A simple score-based strategy to improve equity of the UK biennial diabetic eye screening protocol among people deemed as low riskMatilda Pitt, Abraham Olvera-Barrios, John Anderson, et al.
BMJ Open|November 15, 2023
What are the perceptions and concerns of people living with diabetes and National Health Service staff around the potential implementation of AI-assisted screening for diabetic eye disease? Development and validation of a survey for use in a secondary care screening settingKathryn Willis, Umar A R Chaudhry, Lakshmi Chandrasekaran, et al.
Diabetes Care|June 10, 2026
Head-to-Head Comparative Evaluation of Four Commercially Available Artificial Intelligence Systems for Detecting Referable Diabetic Retinopathy in a Tanzanian PopulationCharles R Cleland, Covadonga Bascaran, William U Makupa, et al.
The Lancet. Digital Health|November 25, 2025
Automated retinal image analysis systems to triage for grading of diabetic retinopathy: a large-scale, open-label, national screening programme in EnglandAlicja R Rudnicka, Royce Shakespeare, Ryan Chambers, et al.
The Lancet. Digital Health|April 4, 2025
Generating evidence to support the role of AI in diabetic eye screening: considerations from the UK National Screening CommitteeTrystan Macdonald, Zhivko Zhelev, Xiaoxuan Liu, et al.
Diabetes Research and Clinical Practice|December 21, 2024
Patient and practitioner perceptions around use of artificial intelligence within the English NHS diabetic eye screening programmeCharlotte Wahlich, Lakshmi Chandrasekaran, Umar A R Chaudhry, et al.
Diabetic Medicine : a Journal of the British Diabetic Association|November 10, 2025
What are the perceptions and concerns of people living with diabetes and National Health Service staff around the potential implementation of AI-assisted screening for diabetic eye disease?Kathryn Willis, Royce Shakespeare, Lakshmi Chandrasekaran, et al.
The British Journal of Ophthalmology|October 24, 2023
Two-year recall for people with no diabetic retinopathy: a multi-ethnic population-based retrospective cohort study using real-world data to quantify the effectAbraham Olvera-Barrios, Alicja R Rudnicka, John Anderson, et al.
BMJ Open Diabetes Research & Care|November 10, 2023
Ethnic disparities in progression rates for sight-threatening diabetic retinopathy in diabetic eye screening: a population-based retrospective cohort studyAbraham Olvera-Barrios, Christopher G Owen, John Anderson, et al.
Pageof 1