Abstract
According to the latest data from the Bureau of Disease Control and Prevention of the National Health and Family Planning Commission, China currently has 199.6 million diabetic patients and has become the world's largest country with diabetes. The prevalence rate is as high as 14.3%, which is much higher than the world average of 5.8%. The primary-level ophthalmic screening service is one of the important tasks to improve primary-level medical services, and the corresponding ophthalmic imaging diagnosis technology is an important support for primary-level medical and health services. Therefore, it is very necessary for us to study the application of artificial intelligence image recognition technology for diabetic retinopathy under the medical consortium mode and to study the precise initial diagnosis, precise referral, and precise follow-up of diabetic retina under the medical conjoined mode, so as to better promote the transformation of the ophthalmology primary service model. Based on this background, in this article, we have proposed and carried out the following solution: (1) diabetes data collation. Based on medical artificial intelligence technology, this paper collected 2,265 electronic medical records from an eye hospital in Ningbo and selected 2,000 qualified medical records for data integration and preprocessing. The contents of electronic medical records mainly include age, gender, and examination records. (2) Establish diabetic retinopathy diagnosis model based on neural network algorithm. This article first uses the classic algorithm of BP neural network for modeling, chooses the Levenberg–Marquardt method as the training function, and selects 10 hidden layer units through comparison experiments. After that, ophthalmologists assessed 80 sets of test results and determined the right diagnosis rate. Finally, this article compares and analyzes the accuracy of the two routes in 80 tests.
Highlights
As people’s living circumstances improve, the number of diabetics increases dramatically [1, 2]
(2) Establish diabetic retinopathy diagnosis model based on neural network algorithm. is article first uses the classic algorithm of back propagation (BP) neural network for modeling, chooses the Levenberg–Marquardt method as the training function, and selects 10 hidden layer units through comparison experiments
According to the statistics of the National Health and Family Planning Commission, there are currently only 36,000 ophthalmologists in China, of which less than 10,000 doctors are engaged in fundus medical services and research. e ratio is less than 10%. rough regular screening of fundus lesions and early diagnosis, nearly 90% of visual impairment and blindness induced by diabetes can be completely avoided [6]
Summary
As people’s living circumstances improve, the number of diabetics increases dramatically [1, 2]. (i) Verify the accuracy of artificial intelligence technology in diagnosing DR detection under the equipment and operating mode of this subject (ii) Analyze the operating efficiency, awareness, and satisfaction of the DR artificial intelligence screening system in Ningbo based on the medical consortium model, and evaluate its actual operating effects (iii) rough the operation of DR artificial intelligence screening mode, improve the diagnosis level of community doctors in ophthalmology, which will help promote the mutual cooperation of all levels of hospitals in the medical system, promote the vertical integration of urban and rural medical resources, and sink high-quality medical resources (iv) rough the analysis of a large sample of screening data, we can draw conclusions about the relationship between the prevalence of DR patients in Ningbo area and factors such as age, environment, gender, as well as the distribution of DR patients in Ningbo area, and the degree of disease classification, etc., to provide government departments with decision-making, and it provides new clinical and basic research directions for the occurrence and development of DR (v) Actively promote the clinical application of hightech in the medical field, and expand the application of interdisciplinary (vi) Use the application of artificial intelligence technology in DR detection to explore the establishment and improvement of the Ningbo DR screening model, improve screening efficiency, expand coverage, so that patients can get treatment in time, and effectively reduce the number of blindness caused by DR in Ningbo e remaining paper is organized as follows.
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