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Abdalla MMI, Mohanraj J. Revolutionizing diabetic retinopathy screening and management: The role of artificial intelligence and machine learning. World J Clin Cases 2025; 13(5): 101306 [PMID: 39959767 DOI: 10.12998/wjcc.v13.i5.101306]
World J Clin Cases. Feb 16, 2025; 13(5): 101306 Published online Feb 16, 2025. doi: 10.12998/wjcc.v13.i5.101306
Revolutionizing diabetic retinopathy screening and management: The role of artificial intelligence and machine learning
Mona Mohamed Ibrahim Abdalla, Jaiprakash Mohanraj
Mona Mohamed Ibrahim Abdalla, Jaiprakash Mohanraj, Department of Human Biology, School of Medicine, International Medical University, Bukit Jalil 57000, Kuala Lumpur, Malaysia
Co-first authors: Mona Mohamed Ibrahim Abdalla and Jaiprakash Mohanraj.
Author contributions: Abdalla MMI and Mohanraj J contribute equally to this article as co-first authors. Abdalla MMI and Mohanraj J performed the research and wrote the paper.
Conflict-of-interest statement: The authors declare no conflict of interest to this paper.
Corresponding author: Mona Mohamed Ibrahim Abdalla, MD, MSc, PhD, Doctor, Senior Lecturer, Department of Human Biology, School of Medicine, International Medical University, No. 126 Jln Jalil Perkasa 19, Bukit Jalil 57000, Kuala Lumpur, Malaysia. monamohamed@imu.edu.my
Received: September 10, 2024 Revised: October 9, 2024 Accepted: November 5, 2024 Published online: February 16, 2025 Processing time: 69 Days and 18.6 Hours
Core Tip
Core Tip: Leveraging artificial intelligence (AI) and machine learning in diabetic retinopathy care can significantly enhance early detection and personalized treatment. Clinicians should embrace AI-driven screening tools that analyze retinal images with high precision, reducing the risk of human error and improving diagnostic accuracy. Implementing predictive analytics can help in identifying patients at higher risk, allowing for timely interventions and tailored treatment plans. To maximize the benefits, healthcare systems must invest in training and integrating these technologies seamlessly into clinical workflows. Collaborations between technologists and healthcare providers are crucial for developing robust, ethical, and equitable AI solutions in ophthalmic care.
