Hyper parameter tuning based gradient boosting algorithm for detection of diabetic retinopathy: an analytical review

Abstract

The pipelines of approaches for classifying diabetic retinopathy were examined in this study. The effort entails developing appropriate transformations and estimators that can be used to automate the process of diabetic retinopathy detection. The segmentation of the blood vessels was done using a hybrid algorithm that uses Otsu and median filter to get the region of interest. Further, ten classifiers were investigated in order to develop an automated pipeline for diabetic retinopathy detection. The ten classifiers were reviewed based on earlier work in a similar setting and on an exploration of new ways for identifying diabetic retinopathy. To overcome the challenge of low volume of dataset, data argumentation was done so that a generic classifier can be configured. Extensive hyper parameter tuning was performed, and it was shown that the gradient boosting approach is the most stable technique for detecting diabetic retinopathy. This was validated using a 10K fold cross validation method on many metrics (accuracy, recall, precision, and v-measure score). Hyper-parameter tuning helped in achieving accuracy of 0.96.

Is it time to consider teleophthalmology as a game-changer in the management of diabetic retinopathy?

“…(81,82) The development of innovative approaches continues. (83)(84)(85)(86)(87)(88)(89)(90)(91)(92)(93) The recent one presented by Zhang et al (83) is based on Deep Graph Correlation Network for grading. Researchers postulated that it has an accuracy near to retinal specialists and more than trained graders.…”

“…Researchers postulated that it has an accuracy near to retinal specialists and more than trained graders. Further improvements are presented by Canayaz, (84) Hu et al, (85) Datta et al, (86) Hassan et al, (87) Venkaiahppalaswamy et al (88) The efforts have been made to develop the hybrid DL system with a segmentation of optic disc and blood vessels. (88) It has been reported that the system achieved 94% accuracy All the reports described above and the findings from other prospective studies (19,21,27,33,39) underscore the potential utility of AI based system in DR screening.…”

Multimode system condition monitoring using sparsity reconstruction for quality control

“…First, the input vector xi={1, 2, 3, ..., N} is transformed into a hidden part represented by the function hi, which is as (1),…”

“…Generally, the analytical methods used in the modeling of dynamic systems do not necessarily meet what is expected by automation engineers, hence the need to rely on statistical methods that provide more information on the processes from existing real data. In this sense, an approach for determining operational states based on data from the statistical analysis system (SAS) can play an important role in the detection and diagnosis of errors [1]. Thus, multivariate statistics tools have been the source of many techniques used in statistical process control (SPC).…”