Soda Mbaye, Aïssatou Aw, El Hadji Malick Sy, Aly Mbara Ka, Jean Pierre Diagne, Hawo Madina Diallo, Audrey Samra, Papa Amadou Ndiaye
{"title":"基于黑色素受试者眼底照片自动筛查糖尿病视网膜病变的人工智能软件评估。","authors":"Soda Mbaye, Aïssatou Aw, El Hadji Malick Sy, Aly Mbara Ka, Jean Pierre Diagne, Hawo Madina Diallo, Audrey Samra, Papa Amadou Ndiaye","doi":"10.1097/IAE.0000000000004310","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>To assess the Gaiha Prio Retino +™Artificial Intelligence (AI) software for detecting diabetic retinopathy (DR).</p><p><strong>Methods: </strong>This prospective study was conducted from March 1, 2021 to September 30, 2022 in the Ophthalmology department of the Abass NDAO Hospital (Dakar, Senegal). The clinical classification of DR was based on American Academy of Ophthalmology's. The clinical results were compared to those obtained from the automated reading of retinophotos taken using Gaiha Prio Retino +™, a software designed to detect DR.</p><p><strong>Results: </strong>The study covered 305 eyes. Referable DR was observed in 104 eyes by the ophthalmologist and in 96 eyes by AI, corresponding with a sensitivity of 92.31%, a specificity of 99%, and an area under the curve (AUC) of 0.989. Vision-threatening DR was detected in 102 eyes by the ophthalmologist and in 94 eyes by AI, with a corresponding sensitivity of 92.16%, specificity of 99.01%, and an AUC of 0.975. Maculopathy was identified in 93 eyes by the ophthalmologist and in 89 eyes by AI, with a corresponding sensitivity of 95.7%, specificity of 97.17%, and an AUC of 0.988.</p><p><strong>Conclusion: </strong>Considering these results, we may conclude that Gaiha Prio Retino +™ is an effective tool for screening referable DR.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Assessment of Artificial Intelligence software for automatic screening of Diabetic Retinopathy based on fundus photographs in Melanoderm subjects.\",\"authors\":\"Soda Mbaye, Aïssatou Aw, El Hadji Malick Sy, Aly Mbara Ka, Jean Pierre Diagne, Hawo Madina Diallo, Audrey Samra, Papa Amadou Ndiaye\",\"doi\":\"10.1097/IAE.0000000000004310\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>To assess the Gaiha Prio Retino +™Artificial Intelligence (AI) software for detecting diabetic retinopathy (DR).</p><p><strong>Methods: </strong>This prospective study was conducted from March 1, 2021 to September 30, 2022 in the Ophthalmology department of the Abass NDAO Hospital (Dakar, Senegal). The clinical classification of DR was based on American Academy of Ophthalmology's. The clinical results were compared to those obtained from the automated reading of retinophotos taken using Gaiha Prio Retino +™, a software designed to detect DR.</p><p><strong>Results: </strong>The study covered 305 eyes. Referable DR was observed in 104 eyes by the ophthalmologist and in 96 eyes by AI, corresponding with a sensitivity of 92.31%, a specificity of 99%, and an area under the curve (AUC) of 0.989. Vision-threatening DR was detected in 102 eyes by the ophthalmologist and in 94 eyes by AI, with a corresponding sensitivity of 92.16%, specificity of 99.01%, and an AUC of 0.975. Maculopathy was identified in 93 eyes by the ophthalmologist and in 89 eyes by AI, with a corresponding sensitivity of 95.7%, specificity of 97.17%, and an AUC of 0.988.</p><p><strong>Conclusion: </strong>Considering these results, we may conclude that Gaiha Prio Retino +™ is an effective tool for screening referable DR.</p>\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/IAE.0000000000004310\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/IAE.0000000000004310","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
Assessment of Artificial Intelligence software for automatic screening of Diabetic Retinopathy based on fundus photographs in Melanoderm subjects.
Purpose: To assess the Gaiha Prio Retino +™Artificial Intelligence (AI) software for detecting diabetic retinopathy (DR).
Methods: This prospective study was conducted from March 1, 2021 to September 30, 2022 in the Ophthalmology department of the Abass NDAO Hospital (Dakar, Senegal). The clinical classification of DR was based on American Academy of Ophthalmology's. The clinical results were compared to those obtained from the automated reading of retinophotos taken using Gaiha Prio Retino +™, a software designed to detect DR.
Results: The study covered 305 eyes. Referable DR was observed in 104 eyes by the ophthalmologist and in 96 eyes by AI, corresponding with a sensitivity of 92.31%, a specificity of 99%, and an area under the curve (AUC) of 0.989. Vision-threatening DR was detected in 102 eyes by the ophthalmologist and in 94 eyes by AI, with a corresponding sensitivity of 92.16%, specificity of 99.01%, and an AUC of 0.975. Maculopathy was identified in 93 eyes by the ophthalmologist and in 89 eyes by AI, with a corresponding sensitivity of 95.7%, specificity of 97.17%, and an AUC of 0.988.
Conclusion: Considering these results, we may conclude that Gaiha Prio Retino +™ is an effective tool for screening referable DR.
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