%0 Journal Article
%T 神经网络算法于消渴内障的应用的研究进展<br>Research Progress on the Application of Neural Network Algorithms in XiaokeNeizhang
%A 孙健豪
%A 郑燕林
%J Hans Journal of Ophthalmology
%P 20-26
%@ 2167-6550
%D 2024
%I Hans Publishing
%R 10.12677/hjo.2024.132004
%X 消渴内障大致相当于西医学的糖尿病性视网膜病变，为消渴病的常见并发症之一，对患者的视力损失及生活质量造成了较大的影响。除了消渴病本身的原发病因素，消渴内障自身的复杂性与难治性也为患者造成了庞大的医疗负担。因此，对于消渴内障的早筛查、早干预成为了防治的第一阵地。近年来，随着光学技术的发展与应用技术的成熟，眼底的情况从以前的“不可知”到现在的“可知”，极大地帮助了对于该疾病的早期筛查及诊断分期。而神经网络算法的加入，使得对于该病的诊断技术达到了“超前预测”的水平。但对于祖国医学而言，消渴内障的辨证尚未完全搭上这班“神经网络算法”的快车。因此，本文拟对近年来神经网络算法于消渴内障病应用的研究进展做系统综述，以启迪其在中医辨证论治的应用，丰富中医望诊的内容，以求得“治未病”之功。<br />
Abstract: XiaokeNeizhang is roughly equivalent to diabetic retinopathy in Western medicine. It is one of the common complications of diabetes and has a great impact on patients' vision loss and quality of life. In addition to the primary causative factors of diabetes, the complexity and refractory of XiaokeNeizhang also impose a huge medical cost on patients. Therefore, early screening and early intervention for XiaokeNeizhang have become the first line of prevention and treatment. In recent years, with the development of optical technology and the maturity of application technology, the condition of the fundus has changed from “unknowable” to “knowable” now, which has greatly helped the early screening and diagnosis and staging of the disease. The addition of neural network algorithms has enabled the diagnosis technology of this disease to reach the level of “prediction”. But for Traditional Chinese Medicine, the syndrome differentiation of XiaokeNeizhang has not yet completely caught up with the express train of this “neural network algorithm”. Therefore, this article intends to conduct a systematic review of the research progress of neural network algorithms in the application of XiaokeNeizhang in recent years, in order to enlighten its application in syndrome differentiation and treatment of Traditional Chinese Medicine, enrich the content of Traditional Chinese Medicine examination, and achieve the effect of “preventing disease”.
%K 消渴内障，深度学习，神经网络，糖尿病性视网膜病变<br>XiaokeNeizhang
%K Deep Learning
%K Neural Network
%K Diabetic Retinopathy
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=89008