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Diabetic Retinopathy Detection

3 papers with code ยท Medical

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Multi-scale Microaneurysms Segmentation Using Embedding Triplet Loss

18 Apr 2019

To enhance the discriminative power of the classification model, we incorporate triplet embedding loss with a selective sampling routine.

DIABETIC RETINOPATHY DETECTION

MedAL: Deep Active Learning Sampling Method for Medical Image Analysis

25 Sep 2018

Active learning techniques can be used to minimize the number of required training labels while maximizing the model's performance. In this work, we propose a novel sampling method that queries the unlabeled examples that maximize the average distance to all training set examples in a learned feature space.

ACTIVE LEARNING DIABETIC RETINOPATHY DETECTION

Replication study: Development and validation of deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs

12 Mar 2018

We have attempted to replicate the main method in 'Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs' published in JAMA 2016; 316(22).

DIABETIC RETINOPATHY DETECTION MEDICAL IMAGE SEGMENTATION MITOSIS DETECTION

Case Study: Explaining Diabetic Retinopathy Detection Deep CNNs via Integrated Gradients

27 Sep 2017

In this report, we applied integrated gradients to explaining a neural network for diabetic retinopathy detection.

DIABETIC RETINOPATHY DETECTION

Zoom-in-Net: Deep Mining Lesions for Diabetic Retinopathy Detection

14 Jun 2017

We propose a convolution neural network based algorithm for simultaneously diagnosing diabetic retinopathy and highlighting suspicious regions.

DIABETIC RETINOPATHY DETECTION

Neural Networks with Manifold Learning for Diabetic Retinopathy Detection

12 Dec 2016

Our experimental results show that neural networks in combination with preprocessing on the images can boost the classification accuracy on this dataset.

DIABETIC RETINOPATHY DETECTION

On The Direct Maximization of Quadratic Weighted Kappa

23 Sep 2015

In recent years, quadratic weighted kappa has been growing in popularity in the machine learning community as an evaluation metric in domains where the target labels to be predicted are drawn from integer ratings, usually obtained from human experts.

DIABETIC RETINOPATHY DETECTION