NEHA SINGH

Data Science Skills

Artificial Intelligence	Statistical Modeling	Big Data
Digital Analytics	Visualization	Python
R	Tableau

Domain Skills

Health Care

Diabetic Retinopathy

Category: Domain Usecases

Sub-Category: Health Care and Pharmaceuticals

Use-case Type: Image Classification

Tags: diabetes,diabetic retinopathy,health care,images,life sciences,unstructured_dataset,VGG,VGG16

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Note: Certain Model Inferences can take long time for the first run (Warmup) and would get faster with the subsequent inferences. We thank you for your patience.

Use Case Summary

Problem Statement
Diabetic retinopathyis the leading cause of blindness in the working-age population of the developed world. It is estimated to affect over 93 million people. With the help of the model, we can detect diabetic retinopathy in an earlier stage in an automated fashion. It will act as a second eye to doctors and reduce the amount of time required by them.

Data Description
Source:https://www.kaggle.com/c/diabetic-retinopathy-detection/data,it has 82 GB of data, with images as with and without Diabetic Retinopathy
Class: Diabetic Retinopathy(2816) and Non-Diabetic Retinopathy(3267)

Model
VGG16

Accuracy
Train Accuracy: 90%
Validation Accuracy: 62%