International Journal of Innovative Research in Advanced Engineering (IJIRAE) ISSN: 2349-2163 August 2022, Volume 9, Issue 8 https:/ / www.ijirae.com/ archives _____________________________________________________________________________________________________________________________________ IJIRAE:: © 2014-22, AM Publications. All rights reserved. https:/ / doi.org/ 10.26562/ ijirae Page -306 AN EXPLAI NABLE AI MODEL FOR DI ABETI C RETINOPATHY DETECTION Deepa Tejashwini M S UG student, Department of CSE Vemana Institute of Technology, Bangalore deepatejashwini.04@gmail.com Maitri S Gaonkar UG student, Department of CSE Vemana Institute of Technology, Bangalore maitrig63@gmail.com Lakshmi H D UG student, Department of CSE Vemana Institute of Technology, Bangalore lakshmisanju6122000@gmail.com A Rosline Mary Assistant Professor, Department of CSE Vemana Institute of Technology, Bangalore roslinemary.a@vemanait.edu.in Madhuri JM UG student, Department of CSE Vemana Institute of Technology, Bangalore madhuri.jcm@gmail.com Publication History Manuscript Reference No: IJIRAE/ RS/ Vol.09/ Issue08/ SPAUAE10107 Research Article | Open Access | Peer-review: Double-blind Peer-reviewed Article ID: IJIRAE/ RS/ Vol.09/ Issue08/ SPAUAE10108 Received Date: 12, July 2022 | Accepted Date: 25, July 2022 | Available Online: 12, August 2022 Volume 2022 | Article ID SPAUE10107 https:/ / www.ijirae.com/ volumes/ Vol9/ iss-08/ 28.SPAUAE10107.pdf Article Citation: Deepa,Maitri,Lakshmi,Mary,Madhuri(2022).An Explainable AI Model for Diabetic Retionopathy Detection. International Journal of Innovative Research in Advanced Engineering (Vol. 9, Issue 8, pp. 306–311). AM Publications, India. doi: https:/ / doi.org/ 10.26562/ ijirae.2022.v0908.28 BibTeX key Academic Editor-Chief: Dr.A.Arul Lawrence Selvakumar Copyright: ©2022 This is an open access article distributed under the terms of the Creative Commons Attribution License; Which Permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Abstract: Diabetes is the most common long-term condition that affects people of all ages due to inadequate insulin production. The appearance of black spots for millennia, interpreting eye pictures, and detecting diabetic retinopathy in its early stages has been a big challenge. The Explainable AI method is to explain the deep learning model that is understandable by humans and trusts the result. This is especially important in safety critical domains like healthcare or security, which replaces manual processes and understanding of the models function by non-technical domain skilled person. Explainable AI is used to describe an AI model, its expected impact and potential biases. It helps characterize model accuracy, fairness, transparency and outcomes in AI-powered decision making. Explainable AI is crucial for an organization in building trust and confidence when putting AI models into production. AI explains ability also helps an organization adopt a responsible approach to AI development. Specifically, the back propagation step is responsible for updating the weights based on its error function. SHAP or SHAPley Additive explanations are a visualization tool that can be used for making a machine learning model more explainable by visualizing its output. It can be used for explaining the prediction of any model by computing the contribution of each feature to the prediction. Keywords: Diabetic Retinopathy, CNN, Explainable AI, SHAP, Microvascular Complication. I. INTRODUCTION Explainable Artificial Intelligence (XAI) is a set of safety procedures and techniques that enable human users to recognize and believe the outcomes and output generated by a machine learning algorithm. One of the most common causes of blindness is Diabetic Retinopathy (DR). The retinal blood vessels of a diabetic patient are mutilated by DR. There are two forms of diabetic retinopathy: non-proliferative diabetic retinopathy (NPDR) and proliferative diabetic retinopathy (PDR). The early tiers' DR is known as NPDR, which is also classified into Mild, Moderate, Severe, and PDR levels. Swelling and rupture of blood vessels within the retina, as well as abnormal scratches on the retina, are all symptoms of DR. Diabetic retinopathy is the main motive of visible impairment and keeps to developing Disability and blindness. A premature survey is critical for reducing the progression of DR and, as a result, preventing the occurrence of blindness.