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Gajaram, Ankitha Mallikarjuna (2022) An Approach to Classify Ocular diseases using Machine Learning and Deep Learning. Masters thesis, Dublin, National College of Ireland.
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Abstract
Ocular diseases are the global phenomena which can be seen across the globe. There are several eye diseases like Cataracts, Glaucoma, Diabetic Retinopathy etc., if neglected, or not diagnosed can lead to blindness or visual impairment. Many surveys conducted revealed poor society knowledge about the ocular disease and their drastic impact on an individual’s life. Over the years, several government organizations as well as few NGOs came forward to spread awareness and educate people the importance of regular eye care routine and check-ups. On the other hand, to detect these diseases it consumes more time and requires to be done manually by highly qualified ophthalmologist. The aim of this research project is to develop a model that could help ophthalmologist in early detection of severe ocular diseases such as cataracts, glaucoma, diabetic retinopathy etc. Four different machine learning and deep learning models are applied, and model with high accuracy can be used to classify the eye disorders. Performance evaluation is done using accuracy score, precision, recall score, f1 score, loss, and accuracy graph. Accuracy score of Random Forest classifier, Support Vector Machine (SVM), k – Nearest Neighbor and Convolution Neural Network is 52%, 59%, 61% and 68% respectively.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Convolution neural network; ocular; cataracts; deep learning; machine learning; glaucoma |
| Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science R Medicine > RE Ophthalmology Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning |
| Divisions: | School of Computing > Master of Science in Data Analytics |
| Depositing User: | Tamara Malone |
| Date Deposited: | 24 Jan 2023 15:20 |
| Last Modified: | 03 Mar 2023 12:19 |
| URI: | https://norma.ncirl.ie/id/eprint/6120 |
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