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Last Posted: May 21, 2024

• Machine Learning-Based Predictive Modeling of Diabetic Nephropathy in Type 2 Diabetes Using Integrated Biomarkers: A Single-Center Retrospective Study.
  Ying Zhu et al. Diabetes Metab Syndr Obes 2024 171987-1997
• Comparison of 21 artificial intelligence algorithms in automated diabetic retinopathy screening using handheld fundus camera.
  Anna-Maria Kubin et al. Ann Med 2024 56(1) 2352018
• Artificial Intelligence (AI) for Early Diagnosis of Retinal Diseases.
  Uday Pratap Singh Parmar et al. Medicina (Kaunas) 2024 60(4)
• Autonomous artificial intelligence versus teleophthalmology for diabetic retinopathy.
  Donatella Musetti et al. Eur J Ophthalmol 2024 11206721241248856
• Development and External Validation of Machine Learning Models for Diabetic Microvascular Complications: Cross-Sectional Study With Metabolites.
  Feng He et al. J Med Internet Res 2024 26e41065
• Patients Perceptions of Artificial Intelligence in a Deep Learning-Assisted Diabetic Retinopathy Screening Event: A Real-World Assessment.
  Fernando Korn Malerbi et al. J Diabetes Sci Technol 2024 19322968241234378
• Automated Machine Learning for Predicting Diabetic Retinopathy Progression From Ultra-Widefield Retinal Images.
  Paolo S Silva et al. JAMA Ophthalmol 2024
• Recommendations for initial diabetic retinopathy screening of diabetic patients using large language model-based artificial intelligence in real-life case scenarios.
  Nikhil Gopalakrishnan et al. Int J Retina Vitreous 2024 10(1) 11
• Autonomous artificial intelligence increases screening and follow-up for diabetic retinopathy in youth: the ACCESS randomized control trial.
  Risa M Wolf et al. Nat Commun 2024 15(1) 421
• Machine Learning Models for Prediction of Diabetic Microvascular Complications.
  Sarah Kanbour et al. J Diabetes Sci Technol 2024 19322968231223726
• Real-world evaluation of smartphone-based artificial intelligence to screen for diabetic retinopathy in Dominica: a clinical validation study.
  Oliver Kemp et al. BMJ Open Ophthalmol 2023 8(1)
• Risk Stratification for Diabetic Retinopathy Screening Order Using Deep Learning: A Multicenter Prospective Study.
  Ashish Bora et al. Transl Vis Sci Technol 2023 12(12) 11
• Clinician-Driven AI: Code-Free Self-Training on Public Data for Diabetic Retinopathy Referral.
  Edward Korot et al. JAMA Ophthalmol 2023
• Artificial intelligence for telemedicine diabetic retinopathy screening: a review.
  Luis Filipe Nakayama et al. Ann Med 2023 55(2) 2258149
• Deep learning detection of diabetic retinopathy in Scotland's diabetic eye screening programme.
  Alan D Fleming et al. Br J Ophthalmol 2023
• Feasibility and accuracy of the screening for diabetic retinopathy using a fundus camera and an artificial intelligence pre-evaluation application.
  A Piatti et al. Acta Diabetol 2023
• Prediction of diabetic kidney disease risk using machine learning models: a population-based cohort study of Asian adults.
  Charumathi Sabanayagam et al. Elife 2023 12
• Smartphone Eye Examination: Artificial Intelligence and Telemedicine.
  Manuel Augusto Pereira Vilela et al. Telemed J E Health 2023
• The Present and Future of Artificial Intelligence-Based Medical Image in Diabetes Mellitus: Focus on Analytical Methods and Limitations of Clinical Use.
  Ji-Won Chun et al. J Korean Med Sci 2023 38(31) e253
• Efficacy of deep learning-based artificial intelligence models in screening and referring patients with diabetic retinopathy and glaucoma.
  Janani Surya et al. Indian J Ophthalmol 2023 71(8) 3039-3045
• Performance of a Support Vector Machine Learning Tool for Diagnosing Diabetic Retinopathy in Clinical Practice.
  Tobias P H Nissen et al. J Pers Med 2023 13(7)
• Adherence of randomised controlled trials using artificial intelligence in ophthalmology to CONSORT-AI guidelines: a systematic review and critical appraisal.
  Niveditha Pattathil et al. BMJ Health Care Inform 2023 30(1)
• AI-Human Hybrid Workflow Enhances Teleophthalmology for the Detection of Diabetic Retinopathy.
  Eliot R Dow et al. Ophthalmol Sci 2023 3(4) 100330
• Single retinal image for diabetic retinopathy screening: performance of a handheld device with embedded artificial intelligence.
  Fernando Marcondes Penha et al. Int J Retina Vitreous 2023 9(1) 41
• Using Deep Learning Architectures for Detection and Classification of Diabetic Retinopathy.
  Cheena Mohanty et al. Sensors (Basel) 2023 23(12)
• Accuracy of Artificial Intelligence in Estimating Best-Corrected Visual Acuity From Fundus Photographs in Eyes With Diabetic Macular Edema.
  William Paul et al. JAMA Ophthalmol 2023
• Determinants of the implementation of artificial intelligence-based screening for diabetic retinopathy-a cross-sectional study with general practitioners in Germany.
  Larisa Wewetzer et al. Digit Health 2023 920552076231176644
• A risk prediction model for type 2 diabetes mellitus complicated with retinopathy based on machine learning and its application in health management.
  Hong Pan et al. Front Med (Lausanne) 2023 101136653
• 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.
  Joseph Mellor et al. Int J Med Inform 2023 175105072
• Clinical validation of a smartphone-based retinal camera for diabetic retinopathy screening.
  Juliana Angélica Estevão de Oliveira et al. Acta Diabetol 2023
• Economic Evaluation of Artificial Intelligence Systems Versus Manual Screening for Diabetic Retinopathy in the United States.
  Harshvardhan Chawla et al. Ophthalmic Surg Lasers Imaging Retina 1-9
• A deep learning nomogram of continuous glucose monitoring data for the risk prediction of diabetic retinopathy in type 2 diabetes.
  Rui Tao et al. Phys Eng Sci Med 2023
• Clinical Applications of Artificial Intelligence in Glaucoma.
  Siamak Yousefi et al. Journal of ophthalmic & vision research 2023 18(1) 97-112
• Implementation of deep learning artificial intelligence in vision-threatening disease screenings for an underserved community during COVID-19.
  Aretha Zhu et al. Journal of telemedicine and telecare 2023 1357633X231158832
• Cost-Utility Analysis of Deep Learning and Trained Human Graders for Diabetic Retinopathy Screening in a Nationwide Program.
  Attasit Srisubat et al. Ophthalmology and therapy 2023
• Segmentation-Assisted Fully Convolutional Neural Network Enhances Deep Learning Performance to Identify Proliferative Diabetic Retinopathy.
  Alam Minhaj et al. Journal of clinical medicine 2023 12(1)
• Test accuracy of artificial intelligence-based grading of fundus images in diabetic retinopathy screening: A systematic review.
  Zhelev Zhivko et al. Journal of medical screening 2023 9691413221144382
• Identification of serum metabolome signatures associated with retinal and renal complications of type 2 diabetes.
  Tomofuji Yoshihiko et al. Communications medicine 2023 3(1) 5
• Deep-Learning-Aided Diagnosis of Diabetic Retinopathy, Age-Related Macular Degeneration, and Glaucoma Based on Structural and Angiographic OCT.
  Zang Pengxiao et al. Ophthalmology science 2022 3(1) 100245
• Simultaneous screening and classification of diabetic retinopathy and age-related macular degeneration based on fundus photos-a prospective analysis of the RetCAD system.
  Skevas Christos et al. International journal of ophthalmology 2022 15(12) 1985-1993

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