International Journal of Science, Engineering and TechnologyAuthors: Nand Kishor, Prof. Akrati Shrivastava, Associate Prof. Dr. Jayshree Boaddh
Abstract: The remarkable success of machine learning has prompted interest in its application to medical imaging diagnosis. Even though state-of-the-art deep learning models have achieved human-level accuracy on the classification of different types of medical data, these models are hardly adopted in clinical workflows, mainly due to their lack of interpretability. This paper has done a deep survey on diabetic retinopathy image classification work done by researchers. Paper has list the features used by the researcher for medical image classification. Further techniques involve in diabetic retinopathy image classification was detailed. Finally various methods of image classification models comparison evaluation parameters were mentioned by the paper.
DOI: http://doi.org/10.5281/zenodo.21305724
