Ophthalmology in China

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Comparison of computer automated screening system with ophthalmologist for grading of diabetic retinopathy

WANG Juan1, CHEN Shu-juan1, DONG Fang-tian2, GONG Di2, TANG Yi1, JIN Meng1, ZHAO Lei1, CHANG Hai-lian3, LIU Feng-tong3, ZHANG Jian3, REN An-na3, ZHANG Fan3   

  1. 1. Daheng Prust Medical Technology Co. Ltd, Beijing 100080, China; 2. Department of Ophthalmology, Peking Union Medical College Hospital, Beijing 100730, China; 3. Department of Ophthalmology, Beijing Pinggu Hospital, Beijing 101200, China
  • Received:2018-01-08 Online:2018-07-25 Published:2018-07-27
  • Contact: CHEN Shu-juan, Email: 452835085@qq.com

Abstract:

Objective Comparison of the sensitivity and specificity of computer automated screening system and ophthalmologist in grading diabetic retinopathy(DR). Design Diagnosis tests. Participants One thousand, one hundred and fifty-five cases of diabetic patients over 40 years old in Beijing Pinggu district were selected. Methods Two-field non-mydriatic fundus photographs center on macular and optic disc were performed. Grading of DR was carried out by two retinal images of one eye. Computer automated screening system carried out by the Software Huiyan from Daheng Prust Medical Technology Co. Ltd. Main Outcome Measure Kappa value, sensitivity, specificity. Results Computer automated screening system and ophthalmologist on the presence of DR with the result of the Kappa values was 0.58. The sensitivity and specificity of the presence of DR on computer automated screening system and ophthalmologist were 87.47% and 74.39% respectively. Computer automated screening system and ophthalmologist on the presence of severe non-proliferative DR with the result of the Kappa values was 0.35. The sensitivity and specificity of the presence of severe non-proliferative DR on computer automated screening system and ophthalmologist were 87.47% and 74.39% respectively. Conclusion These results show that computer automated screening system can efficiently screen retinal images from diabetes populations to reduce the workload of doctors. (Ophthalmol CHN, 2018, 27: 254-257)

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