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Application of machine learning algorithms on diabetic retinopathy

机译:机器学习算法在糖尿病性视网膜病变中的应用

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摘要

Diabatic Retinopathy (DR) is one of the leading cause of sight inefficiency for diabetic patients. The clinical diagnostic results and several outcome of eye testing methods reviled a set of observations that eases the decision making in the case of diabetic retinopathy for the doctor, therapist. Machine learning, a branch of artificial intelligence is applied in clinical data analytic as it can detect patterns in data, and then use these uncovered patterns to predict future data or perform some kind of decision making under uncertainty. In case of DR finding the co-relation between the depth of affection and the clinical result is very much critical, as several parameters are need to be taken into consideration for optimal decision making by the therapist. In this paper we have reviewed the performance of a set of machine learning algorithms and verify their performance for a particular DR data set.
机译:绝热性视网膜病(DR)是糖尿病患者视力低下的主要原因之一。眼部检查方法的临床诊断结果和几种结果要求获得一系列观察结果,这些发现可以简化医生,治疗师在糖尿病性视网膜病变中的决策。机器学习是人工智能的一个分支,它可以在临床数据分析中应用,因为它可以检测数据中的模式,然后使用这些未发现的模式来预测未来的数据或在不确定的情况下执行某种决策。在DR的情况下,发现感染深度与临床结果之间的相互关系非常关键,因为治疗师的最佳决策需要考虑多个参数。在本文中,我们回顾了一组机器学习算法的性能,并验证了它们在特定灾难恢复数据集中的性能。

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