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References from Incremental value of AI-derived retinal vascular parameters for predicting incident type 2 diabetes. Local targets link to admitted publications; unresolved targets remain external evidence.
Unresolved reference
External reference
Survey of diabetes risk assessment tools: concepts, structure and performance
10.1002/dmrr.2296 · 2012 · External reference
Performance of the Finnish Diabetes Risk Score (FINDRISC) and Modified Asian FINDRISC (ModAsian FINDRISC) for screening of undiagnosed type 2 diabetes mellitus and dysglycaemia in primary care
10.1016/j.pcd.2020.02.008 · 2020 · External reference
Microvascular dysfunction in diabetes mellitus and cardiometabolic disease
10.1210/endrev/bnaa025 · 2021 · External reference
Microvascular dysfunction is associated with a higher incidence of type 2 diabetes mellitus: a systematic review and meta-analysis
10.1161/atvbaha.112.300291 · 2012 · External reference
Obesity, metabolic syndrome, impaired fasting glucose, and microvascular dysfunction: a principal component analysis approach
10.1186/1471-2261-12-102 · 2012 · External reference
Retinal arteriolar narrowing and risk of diabetes mellitus in middle-aged persons
10.1001/jama.287.19.2528 · 2002 · External reference
Retinal vascular caliber and the long-term risk of diabetes and impaired fasting glucose: the Blue Mountains Eye Study
10.1080/10739680701812220 · 2008 · External reference
Are retinal arteriolar or venular diameters associated with markers for cardiovascular disorders? The Rotterdam Study
10.1167/iovs.03-1390 · 2004 · External reference
Association between retinal vessel caliber and arterial stiffness in a population comprised of normotensive to early-stage hypertensive individuals
10.1093/ajh/hpu074 · 2014 · External reference
Association of retinal vessel calibers and longitudinal changes in arterial stiffness: the Nagahama study
10.1097/hjh.0000000000001602 · 2018 · External reference
Artificial intelligence and deep learning in ophthalmology
10.1136/bjophthalmol-2018-313173 · 2019 · External reference
Retinal image analysis: concepts, applications and potential
10.1016/j.preteyeres.2005.07.001 · 2006 · External reference
Retinal vascular fractal dimension and its relationship with cardiovascular and ocular risk factors
10.1016/j.ajo.2012.04.016 · 2012 · External reference
A deep learning algorithm based on fundus photographs to measure retinal vascular parameters and their additional value beyond the CAIDE risk score for predicting 14-year dementia risk
2025 · External reference
UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age
10.1371/journal.pmed.1001779 · 2015 · External reference
Cohort profile of the UK Biobank: diagnosis and characteristics of cerebrovascular disease
10.1136/bmjopen-2015-009161 · 2016 · External reference
Association between coronary artery calcification and cognitive function in a Chinese community-based population
2021 · External reference
The short-term impacts of COVID-2019 on depressive symptoms and cognitive decline: A community-based cohort study
2025 · External reference
Associations between atherosclerosis and subsequent cognitive decline: a prospective cohort study
10.1161/jaha.124.036696 · 2024 · External reference
Frequency and distribution of refractive error in adult life: methodology and findings of the UK biobank study
10.1371/journal.pone.0139780 · 2015 · External reference
Cohort profile: design and methods in the eye and vision consortium of UK Biobank
10.1136/bmjopen-2018-025077 · 2019 · External reference
Deep learning algorithm using fundus photographs for 10-year risk assessment of ischemic cardiovascular diseases in China
10.1016/j.scib.2021.08.016 · 2022 · External reference
Revised formulas for summarizing retinal vessel diameters
10.1076/ceyr.27.3.143.16049 · 2003 · External reference
Associations of retinal microvascular diameters and tortuosity with blood pressure and arterial stiffness: United Kingdom biobank
10.1161/hypertensionaha.119.13752 · 2019 · External reference
Comparison of digital and film grading of diabetic retinopathy severity in the diabetes control and complications trial/epidemiology of diabetes interventions and complications study
10.1001/archophthalmol.2011.136 · 2011 · External reference
Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors
10.1002/(sici)1097-0258(19960229)15:4<361::aid-sim168>3.0.co;2-4 · 1996 · External reference
Assessing the performance of prediction models: a framework for traditional and novel measures
10.1097/ede.0b013e3181c30fb2 · 2010 · External reference
Decision curve analysis: a novel method for evaluating prediction models
10.1177/0272989x06295361 · 2006 · External reference
Calibration: the Achilles heel of predictive analytics
10.1186/s12916-019-1466-7 · 2019 · External reference
Retinal arteriolar narrowing, hypertension, and subsequent risk of diabetes mellitus
10.1001/archinte.165.9.1060 · 2005 · External reference
Diabetic microvascular disease: an endocrine society scientific statement
10.1210/jc.2017-01922 · 2017 · External reference
Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs
10.1001/jama.2016.17216 · 2016 · External reference
10.1117/12.2549574
10.1117/12.2549574 · External reference
10.1007/978-3-319-68195-5_86
10.1007/978-3-319-68195-5_86 · External reference
Relationship between diabetes and grayscale fractal dimensions of retinal vasculature in the Indian population
10.1186/1471-2415-14-152 · 2014 · External reference
Fractal dimensional analysis of optical coherence tomography angiography in eyes with diabetic retinopathy
10.1167/iovs.16-19656 · 2016 · External reference
10.1161/hypertensionaha.107.089680
10.1161/hypertensionaha.107.089680 · External reference