{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T00:37:26Z","timestamp":1722991046405},"reference-count":68,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["clinicalkey.fr","clinicalkey.jp","clinicalkey.es","clinicalkey.com.au","clinicalkey.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Artificial Intelligence in Medicine"],"published-print":{"date-parts":[[2024,8]]},"DOI":"10.1016\/j.artmed.2024.102927","type":"journal-article","created":{"date-parts":[[2024,6,28]],"date-time":"2024-06-28T23:30:03Z","timestamp":1719617403000},"page":"102927","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Enhancing stroke risk and prognostic timeframe assessment with deep learning and a broad range of retinal biomarkers"],"prefix":"10.1016","volume":"154","author":[{"ORCID":"http:\/\/orcid.org\/0009-0005-6565-9011","authenticated-orcid":false,"given":"Shvat","family":"Messica","sequence":"first","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0003-0917-1319","authenticated-orcid":false,"given":"Dan","family":"Presil","sequence":"additional","affiliation":[]},{"given":"Yaacov","family":"Hoch","sequence":"additional","affiliation":[]},{"given":"Tsvi","family":"Lev","sequence":"additional","affiliation":[]},{"given":"Aviel","family":"Hadad","sequence":"additional","affiliation":[]},{"given":"Or","family":"Katz","sequence":"additional","affiliation":[]},{"given":"David R.","family":"Owens","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.artmed.2024.102927_b1","article-title":"Trends in stroke incidence in high-income countries in the 21st century","author":"Li","year":"2020","journal-title":"Stroke"},{"issue":"5","key":"10.1016\/j.artmed.2024.102927_b2","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1016\/S1474-4422(19)30034-1","article-title":"Global, regional, and national burden of stroke, 1990\u20132016: a systematic analysis for the global burden of disease study 2016","volume":"18","author":"Johnson","year":"2019","journal-title":"Lancet Neurol"},{"issue":"12","key":"10.1016\/j.artmed.2024.102927_b3","doi-asserted-by":"crossref","first-page":"1160","DOI":"10.1016\/S1474-4422(23)00277-6","article-title":"Pragmatic solutions to reduce the global burden of stroke: a world stroke organization\u2013lancet neurology commission","volume":"22","author":"Feigin","year":"2023","journal-title":"Lancet Neurol"},{"issue":"3","key":"10.1016\/j.artmed.2024.102927_b4","doi-asserted-by":"crossref","first-page":"670","DOI":"10.1161\/STROKEAHA.121.036263","article-title":"Evidence-based disparities in stroke care metrics and outcomes in the United States: a systematic review","volume":"53","author":"Ikeme","year":"2022","journal-title":"Stroke"},{"issue":"22","key":"10.1016\/j.artmed.2024.102927_b5","doi-asserted-by":"crossref","first-page":"2644","DOI":"10.1001\/archinte.165.22.2644","article-title":"Metabolic syndrome vs framingham risk score for prediction of coronary heart disease, stroke, and type 2 diabetes mellitus","volume":"165","author":"Wannamethee","year":"2005","journal-title":"Arch Internal Med"},{"issue":"29","key":"10.1016\/j.artmed.2024.102927_b6","doi-asserted-by":"crossref","first-page":"2315","DOI":"10.1093\/eurheartj\/ehw106","volume":"37","author":"Piepoli","year":"2016","journal-title":"Eur Heart J"},{"issue":"1","key":"10.1016\/j.artmed.2024.102927_b7","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.amjmed.2020.07.013","article-title":"Retinal microvascular signs as screening and prognostic factors for cardiac disease: a systematic review of current evidence","volume":"134","author":"Allon","year":"2021","journal-title":"Am J Med"},{"issue":"4","key":"10.1016\/j.artmed.2024.102927_b8","doi-asserted-by":"crossref","first-page":"732","DOI":"10.1097\/HJH.0000000000003071","article-title":"Retinal microvascular abnormalities and risks of incident stroke and its subtypes: The circulatory risk in communities study","volume":"40","author":"Li","year":"2022","journal-title":"J Hypertens"},{"key":"10.1016\/j.artmed.2024.102927_b9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11883-020-0834-2","article-title":"Association between caliber of retinal vessels and cardiovascular disease: a systematic review and meta-analysis","volume":"22","author":"Guo","year":"2020","journal-title":"Curr Atheroscler Rep"},{"key":"10.1016\/j.artmed.2024.102927_b10","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.preteyeres.2017.01.001","article-title":"Imaging retina to study dementia and stroke","volume":"57","author":"Cheung","year":"2017","journal-title":"Prog Retin Eye Res"},{"key":"10.1016\/j.artmed.2024.102927_b11","doi-asserted-by":"crossref","DOI":"10.1155\/2016\/6138659","article-title":"Retinal vessel diameters and their relationship with cardiovascular risk and all-cause mortality in the inter99 eye study: a 15-year follow-up","volume":"2016","author":"Drobnjak","year":"2016","journal-title":"J Ophthalmol"},{"issue":"1","key":"10.1016\/j.artmed.2024.102927_b12","doi-asserted-by":"crossref","first-page":"19053","DOI":"10.1038\/srep19053","article-title":"Retinal information is independently associated with cardiovascular disease in patients with type 2 diabetes","volume":"6","author":"Guo","year":"2016","journal-title":"Sci Rep"},{"issue":"7","key":"10.1016\/j.artmed.2024.102927_b13","doi-asserted-by":"crossref","first-page":"1960","DOI":"10.1016\/j.jstrokecerebrovasdis.2018.02.041","article-title":"Retinal microvascular abnormalities as surrogate markers of cerebrovascular ischemic disease: a meta-analysis","volume":"27","author":"Dumitrascu","year":"2018","journal-title":"J Stroke Cerebrovasc Dis"},{"issue":"11","key":"10.1016\/j.artmed.2024.102927_b14","doi-asserted-by":"crossref","first-page":"2862","DOI":"10.1161\/STROKEAHA.116.014998","article-title":"Association of retinopathy and retinal microvascular abnormalities with stroke and cerebrovascular disease","volume":"47","author":"Hughes","year":"2016","journal-title":"Stroke"},{"issue":"10","key":"10.1016\/j.artmed.2024.102927_b15","doi-asserted-by":"crossref","first-page":"2215","DOI":"10.1007\/s00125-021-05499-z","article-title":"Retinal arteriolar tortuosity and fractal dimension are associated with long-term cardiovascular outcomes in people with type 2 diabetes","volume":"64","author":"Sandoval-Garcia","year":"2021","journal-title":"Diabetologia"},{"key":"10.1016\/j.artmed.2024.102927_b16","article-title":"Reduced retinal microvascular perfusion in patients with stroke detected by optical coherence tomography angiography","volume":"13","author":"Liu","year":"2021","journal-title":"Front Aging Neurosci"},{"key":"10.1016\/j.artmed.2024.102927_b17","doi-asserted-by":"crossref","DOI":"10.3389\/fneur.2021.626996","article-title":"Association of diabetic retinopathy with stroke: a systematic review and meta-analysis","volume":"12","author":"Hu","year":"2021","journal-title":"Front Neurol"},{"key":"10.1016\/j.artmed.2024.102927_b18","doi-asserted-by":"crossref","DOI":"10.3389\/fmed.2022.945245","article-title":"Diabetic retinopathy as a predictor of cardiovascular morbidity and mortality in subjects with type 2 diabetes","volume":"9","author":"Barrot","year":"2022","journal-title":"Front Med"},{"issue":"12","key":"10.1016\/j.artmed.2024.102927_b19","doi-asserted-by":"crossref","first-page":"3733","DOI":"10.1161\/STROKEAHA.120.030350","article-title":"Diabetic retinopathy and risk of stroke: a secondary analysis of the ACCORD eye study","volume":"51","author":"Wong","year":"2020","journal-title":"Stroke"},{"key":"10.1016\/j.artmed.2024.102927_b20","doi-asserted-by":"crossref","DOI":"10.3389\/fcvm.2022.945421","article-title":"Diabetic retinopathy predicts cardiovascular disease independently of subclinical atherosclerosis in individuals with type 2 diabetes: A prospective cohort study","volume":"9","author":"Castelblanco","year":"2022","journal-title":"Front Cardiovasc Med"},{"issue":"3","key":"10.1016\/j.artmed.2024.102927_b21","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1038\/s41551-018-0195-0","article-title":"Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning","volume":"2","author":"Poplin","year":"2018","journal-title":"Nat Biomed Eng"},{"key":"10.1016\/j.artmed.2024.102927_b22","series-title":"2021 43rd annual international conference of the IEEE engineering in medicine & biology society","first-page":"3873","article-title":"Towards stroke biomarkers on fundus retinal imaging: a comparison between vasculature embeddings and general purpose convolutional neural networks","author":"Coronado","year":"2021"},{"issue":"5","key":"10.1016\/j.artmed.2024.102927_b23","doi-asserted-by":"crossref","first-page":"e306","DOI":"10.1016\/S2589-7500(21)00043-1","article-title":"Deep-learning-based cardiovascular risk stratification using coronary artery calcium scores predicted from retinal photographs","volume":"3","author":"Rim","year":"2021","journal-title":"Lancet Digit Health"},{"issue":"1","key":"10.1016\/j.artmed.2024.102927_b24","doi-asserted-by":"crossref","first-page":"466","DOI":"10.1186\/s12916-022-02620-w","article-title":"Retinal age gap as a predictive biomarker of stroke risk","volume":"20","author":"Zhu","year":"2022","journal-title":"BMC Med"},{"key":"10.1016\/j.artmed.2024.102927_b25","doi-asserted-by":"crossref","DOI":"10.3389\/fneur.2022.916966","article-title":"Ischemic and haemorrhagic stroke risk estimation using a machine-learning-based retinal image analysis","volume":"13","author":"Qu","year":"2022","journal-title":"Front Neurol"},{"issue":"1","key":"10.1016\/j.artmed.2024.102927_b26","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1038\/s42256-021-00427-7","article-title":"Predicting myocardial infarction through retinal scans and minimal personal information","volume":"4","author":"Diaz-Pinto","year":"2022","journal-title":"Nat Mach Intell"},{"key":"10.1016\/j.artmed.2024.102927_b27","first-page":"1","article-title":"A foundation model for generalizable disease detection from retinal images","author":"Zhou","year":"2023","journal-title":"Nature"},{"key":"10.1016\/j.artmed.2024.102927_b28","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijmedinf.2023.105072","article-title":"Can deep learning on retinal images augment known risk factors for cardiovascular disease prediction in diabetes? A prospective cohort study from the national screening programme in Scotland","volume":"175","author":"Mellor","year":"2023","journal-title":"Int J Med Inform"},{"issue":"7","key":"10.1016\/j.artmed.2024.102927_b29","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1167\/tvst.11.7.12","article-title":"AutoMorph: Automated retinal vascular morphology quantification via a deep learning pipeline","volume":"11","author":"Zhou","year":"2022","journal-title":"Transl Vis Sci Technol"},{"key":"10.1016\/j.artmed.2024.102927_b30","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.neucom.2020.06.143","article-title":"A refined equilibrium generative adversarial network for retinal vessel segmentation","volume":"437","author":"Zhou","year":"2021","journal-title":"Neurocomputing"},{"key":"10.1016\/j.artmed.2024.102927_b31","series-title":"Medical image computing and computer assisted intervention\u2013MICCAI 2021: 24th international conference, Strasbourg, France, September 27\u2013October 1, 2021, proceedings, part i 24","first-page":"482","article-title":"Learning to address intra-segment misclassification in retinal imaging","author":"Zhou","year":"2021"},{"key":"10.1016\/j.artmed.2024.102927_b32","first-page":"12077","article-title":"SegFormer: Simple and efficient design for semantic segmentation with transformers","volume":"34","author":"Xie","year":"2021","journal-title":"Adv Neural Inf Process Syst"},{"key":"10.1016\/j.artmed.2024.102927_b33","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2019.101570","article-title":"Refuge challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs","volume":"59","author":"Orlando","year":"2020","journal-title":"Med Image Anal"},{"key":"10.1016\/j.artmed.2024.102927_b34","series-title":"2020 international joint conference on neural networks","first-page":"1","article-title":"G1020: A benchmark retinal fundus image dataset for computer-aided glaucoma detection","author":"Bajwa","year":"2020"},{"issue":"1","key":"10.1016\/j.artmed.2024.102927_b35","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1038\/s41597-022-01388-1","article-title":"PAPILA: Dataset with fundus images and clinical data of both eyes of the same patient for glaucoma assessment","volume":"9","author":"Kovalyk","year":"2022","journal-title":"Sci Data"},{"key":"10.1016\/j.artmed.2024.102927_b36","doi-asserted-by":"crossref","DOI":"10.1016\/j.artmed.2019.101758","article-title":"Ophthalmic diagnosis using deep learning with fundus images\u2013A critical review","volume":"102","author":"Sengupta","year":"2020","journal-title":"Artif Intell Med"},{"issue":"1","key":"10.1016\/j.artmed.2024.102927_b37","doi-asserted-by":"crossref","first-page":"4494","DOI":"10.1038\/s41598-024-55056-y","article-title":"Automated vertical cup-to-disc ratio determination from fundus images for glaucoma detection","volume":"14","author":"Gao","year":"2024","journal-title":"Sci Rep"},{"key":"10.1016\/j.artmed.2024.102927_b38","doi-asserted-by":"crossref","DOI":"10.3389\/fneur.2022.1034976","article-title":"Association between glaucoma and risk of stroke: A systematic review and meta-analysis","volume":"13","author":"Wang","year":"2023","journal-title":"Front Neurol"},{"issue":"1","key":"10.1016\/j.artmed.2024.102927_b39","doi-asserted-by":"crossref","first-page":"4828","DOI":"10.1038\/s41467-021-25138-w","article-title":"Automatic detection of 39 fundus diseases and conditions in retinal photographs using deep neural networks","volume":"12","author":"Cen","year":"2021","journal-title":"Nat Commun"},{"issue":"7","key":"10.1016\/j.artmed.2024.102927_b40","doi-asserted-by":"crossref","first-page":"917","DOI":"10.1001\/archopht.125.7.917","article-title":"Visual impairment, age-related macular degeneration, cataract, and long-term mortality: the blue mountains eye study","volume":"125","author":"Cugati","year":"2007","journal-title":"Arch Ophthalmol"},{"issue":"1","key":"10.1016\/j.artmed.2024.102927_b41","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1080\/09286580600878844","article-title":"Rationale and methodology for a population-based study of eye diseases in malay people: The Singapore malay eye study (SiMES)","volume":"14","author":"Foong","year":"2007","journal-title":"Ophthalmic Epidemiol."},{"issue":"6","key":"10.1016\/j.artmed.2024.102927_b42","doi-asserted-by":"crossref","first-page":"1401","DOI":"10.1177\/19322968211042665","article-title":"Evaluation of a new neural network classifier for diabetic retinopathy","volume":"16","author":"Katz","year":"2022","journal-title":"J Diabetes Sci Technol"},{"key":"10.1016\/j.artmed.2024.102927_b43","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2023.106647","article-title":"Automatic vessel crossing and bifurcation detection based on multi-attention network vessel segmentation and directed graph search","volume":"155","author":"Wang","year":"2023","journal-title":"Comput Biol Med"},{"issue":"1","key":"10.1016\/j.artmed.2024.102927_b44","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12886-022-02629-y","article-title":"Changes in retinal vascular bifurcation in eyes with myopia","volume":"22","author":"Sun","year":"2022","journal-title":"BMC Ophthalmol"},{"key":"10.1016\/j.artmed.2024.102927_b45","doi-asserted-by":"crossref","unstructured":"Liu Zhuang, Mao Hanzi, Wu Chao-Yuan, Feichtenhofer Christoph, Darrell Trevor, Xie Saining. A convnet for the 2020s. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. 2022, p. 11976\u201386.","DOI":"10.1109\/CVPR52688.2022.01167"},{"issue":"7","key":"10.1016\/j.artmed.2024.102927_b46","doi-asserted-by":"crossref","first-page":"1655","DOI":"10.1109\/TPAMI.2018.2846566","article-title":"Fine-tuning CNN image retrieval with no human annotation","volume":"41","author":"Radenovi\u0107","year":"2018","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"10.1016\/j.artmed.2024.102927_b47","series-title":"2013 35th annual international conference of the IEEE engineering in medicine and biology society","first-page":"5865","article-title":"Automated quantification of retinal arteriovenous nicking from colour fundus images","author":"Nguyen","year":"2013"},{"key":"10.1016\/j.artmed.2024.102927_b48","series-title":"2014 36th annual international conference of the IEEE engineering in medicine and biology society","first-page":"6324","article-title":"An effective automated system for grading severity of retinal arteriovenous nicking in colour retinal images","author":"Roy","year":"2014"},{"issue":"25_suppl_2","key":"10.1016\/j.artmed.2024.102927_b49","doi-asserted-by":"crossref","first-page":"S49","DOI":"10.1161\/01.cir.0000437741.48606.98","article-title":"2013 ACC\/AHA guideline on the assessment of cardiovascular risk: a report of the American college of cardiology\/American heart association task force on practice guidelines","volume":"129","author":"Goff","year":"2014","journal-title":"Circulation"},{"issue":"3","key":"10.1016\/j.artmed.2024.102927_b50","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pmed.1001779","article-title":"UK biobank: An open access resource for identifying the causes of a wide range of complex diseases of middle and old age","volume":"12","author":"Sudlow","year":"2015","journal-title":"PLoS Med"},{"issue":"2","key":"10.1016\/j.artmed.2024.102927_b51","doi-asserted-by":"crossref","DOI":"10.1136\/bmjopen-2018-025077","article-title":"Cohort profile: design and methods in the eye and vision consortium of UK biobank","volume":"9","author":"Chua","year":"2019","journal-title":"BMJ Open"},{"key":"10.1016\/j.artmed.2024.102927_b52","doi-asserted-by":"crossref","first-page":"837","DOI":"10.2307\/2531595","article-title":"Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach","author":"DeLong","year":"1988","journal-title":"Biometrics"},{"issue":"7","key":"10.1016\/j.artmed.2024.102927_b53","doi-asserted-by":"crossref","first-page":"1960","DOI":"10.1016\/j.jstrokecerebrovasdis.2018.02.041","article-title":"Retinal microvascular abnormalities as surrogate markers of cerebrovascular ischemic disease: a meta-analysis","volume":"27","author":"Dumitrascu","year":"2018","journal-title":"J Stroke Cerebrovasc Dis"},{"key":"10.1016\/j.artmed.2024.102927_b54","first-page":"1","article-title":"Retinal imaging for the assessment of stroke risk: a systematic review","author":"Girach","year":"2024","journal-title":"J Neurol"},{"key":"10.1016\/j.artmed.2024.102927_b55","doi-asserted-by":"crossref","DOI":"10.1016\/j.artmed.2024.102779","article-title":"Opportunities and challenges of artificial intelligence and distributed systems to improve the quality of healthcare service","author":"Aminizadeh","year":"2024","journal-title":"Artif Intell Med"},{"key":"10.1016\/j.artmed.2024.102927_b56","doi-asserted-by":"crossref","first-page":"1499","DOI":"10.1007\/s11357-020-00252-7","article-title":"Retinal biomarkers for Alzheimer\u2019s disease and vascular cognitive impairment and dementia (VCID): implication for early diagnosis and prognosis","volume":"42","author":"Czak\u00f3","year":"2020","journal-title":"Geroscience"},{"issue":"21","key":"10.1016\/j.artmed.2024.102927_b57","doi-asserted-by":"crossref","first-page":"15834","DOI":"10.3390\/ijms242115834","article-title":"Potential retinal biomarkers in Alzheimer\u2019s disease","volume":"24","author":"Garc\u00eda-Berm\u00fadez","year":"2023","journal-title":"Int J Mol Sci"},{"key":"10.1016\/j.artmed.2024.102927_b58","doi-asserted-by":"crossref","DOI":"10.1016\/j.arr.2021.101361","article-title":"Retinal biomarkers in Alzheimer\u2019s disease and mild cognitive impairment: A systematic review and meta-analysis","volume":"69","author":"Ge","year":"2021","journal-title":"Ageing Res Rev"},{"issue":"4","key":"10.1016\/j.artmed.2024.102927_b59","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1159\/000487053","article-title":"Peripheral retinal imaging biomarkers for Alzheimer\u2019s disease: a pilot study","volume":"59","author":"Csincsik","year":"2018","journal-title":"Ophthalmic Res"},{"issue":"5","key":"10.1016\/j.artmed.2024.102927_b60","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1053\/j.ajkd.2022.09.018","article-title":"Association of retinal age gap and risk of kidney failure: A UK biobank study","volume":"81","author":"Zhang","year":"2023","journal-title":"Am J Kidney Dis"},{"key":"10.1016\/j.artmed.2024.102927_b61","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1007\/s00592-020-01621-6","article-title":"Retinal image measurements and their association with chronic kidney disease in Chinese patients with type 2 diabetes: the NCD study","volume":"58","author":"Xu","year":"2021","journal-title":"Acta Diabetol"},{"issue":"7","key":"10.1016\/j.artmed.2024.102927_b62","doi-asserted-by":"crossref","first-page":"665","DOI":"10.3390\/jpm11070665","article-title":"Retinal vascular signs as screening and prognostic factors for chronic kidney disease: a systematic review and meta-analysis of current evidence","volume":"11","author":"Aronov","year":"2021","journal-title":"J Pers Med"},{"issue":"1","key":"10.1016\/j.artmed.2024.102927_b63","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1186\/s12882-023-03386-w","article-title":"Retinal changes and cardiac biomarker assessment in relation to chronic kidney disease: a single centre study","volume":"24","author":"Mustafar","year":"2023","journal-title":"BMC Nephrol"},{"issue":"1","key":"10.1016\/j.artmed.2024.102927_b64","doi-asserted-by":"crossref","DOI":"10.1117\/1.JMI.4.1.014503","article-title":"DR HAGIS\u2014a fundus image database for the automatic extraction of retinal surface vessels from diabetic patients","volume":"4","author":"Holm","year":"2017","journal-title":"J Med Imaging"},{"issue":"12","key":"10.1016\/j.artmed.2024.102927_b65","doi-asserted-by":"crossref","first-page":"2631","DOI":"10.1109\/TMI.2016.2587062","article-title":"Robust retinal vessel segmentation via locally adaptive derivative frames in orientation scores","volume":"35","author":"Zhang","year":"2016","journal-title":"IEEE Trans Med Imaging"},{"issue":"3","key":"10.1016\/j.artmed.2024.102927_b66","doi-asserted-by":"crossref","first-page":"25","DOI":"10.3390\/data3030025","article-title":"Indian diabetic retinopathy image dataset (IDRiD): a database for diabetic retinopathy screening research","volume":"3","author":"Porwal","year":"2018","journal-title":"Data"},{"issue":"4","key":"10.1016\/j.artmed.2024.102927_b67","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1109\/TMI.2004.825627","article-title":"Ridge-based vessel segmentation in color images of the retina","volume":"23","author":"Staal","year":"2004","journal-title":"IEEE Trans Med Imaging"},{"year":"2023","series-title":"TJDR: A high-quality diabetic retinopathy pixel-level annotation dataset","author":"Mao","key":"10.1016\/j.artmed.2024.102927_b68"}],"container-title":["Artificial Intelligence in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0933365724001696?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0933365724001696?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2024,8,6]],"date-time":"2024-08-06T10:44:54Z","timestamp":1722941094000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0933365724001696"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8]]},"references-count":68,"alternative-id":["S0933365724001696"],"URL":"https:\/\/doi.org\/10.1016\/j.artmed.2024.102927","relation":{},"ISSN":["0933-3657"],"issn-type":[{"type":"print","value":"0933-3657"}],"subject":[],"published":{"date-parts":[[2024,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Enhancing stroke risk and prognostic timeframe assessment with deep learning and a broad range of retinal biomarkers","name":"articletitle","label":"Article Title"},{"value":"Artificial Intelligence in Medicine","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.artmed.2024.102927","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2024 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"102927"}}