人工神经网络在青光眼早期诊断中的应用

E. N. Komarovskikh, E. V. Podtynnykh
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引用次数: 0

摘要

目的:总结人工神经网络(ANW)在原发性开角型青光眼(POAG)早期诊断中的发展和应用经验。材料和方法。共有690名患者(918只眼睛)接受了测试。训练临床组459例(459眼),其中初期POAG 369眼,无青光眼90眼。试验临床组131例(131眼),其中POAG患者110眼,非青光眼21眼。使用ANW对328只眼睛进行了最终诊断测试,研究人员不知道这些眼睛的诊断结果,这些眼睛属于疑似POAG患者。诊断复合体包括一套最佳必要的研究技术。在疑似青光眼的患者中,ANW诊断出青光眼的198只眼睛(60.4%)100%确定。76只眼(23.2%)为非青光眼或“健康”眼;将疑似青光眼患者的54只眼确定为“可疑”,然后用由5个神经网络组成的神经网络池对其进行重新测试。根据复检结果,28只眼(51.9%)为青光眼,26只眼(48.1%)为非青光眼,即健康。我们的经验表明,人工神经网络对医生或患者没有危险,可以被视为早期POAG诊断的非常方便的工具。
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Using artificial neural networks for early diagnosis of glaucoma
Purpose: to summarize the experience of the development and application of artificial neural networks (ANW) in early diagnosis of primary open-angle glaucoma (POAG).Material and methods. A total of 690 patients (918 eyes) were tested. The training clinical group consisted of 459 clinical examples (459 eyes), of which 369 eyes had an initial stage of POAG and 90 eyes had no glaucoma. The testing clinical group was represented by 131 examples (131 eyes), of which 110 eyes belonged to patients with POAG and 21 eyes were without glaucoma. The final diagnostic testing using ANW was conducted on 328 eyes with the diagnosis unknown to the researchers, which belonged to people with suspected POAG. The diagnostic complex included an optimally necessary set of research techniques.Results. ANW identified glaucoma in 198 eyes out of those with suspected glaucoma (60.4 %) with 100 % certainty. 76 eyes (23.2 %) were classified as non-glaucoma, or “healthy”; 54 eyes of the suspected glaucoma patients were identified as “doubtful”, whereupon they were retested by a neural network pool consisting of 5 neural networks. According to the results of the retesting, 28 eyes, or 51.9 % of the “doubtful” ones were identified as having glaucoma, whereas 26 eyes (48.1 %) were identified as non-glaucomatous, i. e. healthy.Conclusion. Our experience suggests that artificial neural networks pose no danger to the doctor or the patient and can be viewed as a very convenient tool for early POAG diagnostics.
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来源期刊
CiteScore
0.50
自引率
0.00%
发文量
107
审稿时长
16 weeks
期刊最新文献
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