Article
Version 1
Preserved in Portico This version is not peer-reviewed
Quantum Machine Learning for Ocular Disease Recognition
Version 1
: Received: 20 March 2023 / Approved: 20 March 2023 / Online: 20 March 2023 (07:20:49 CET)
How to cite: Topaloglu, R.O. Quantum Machine Learning for Ocular Disease Recognition. Preprints 2023, 2023030350. https://doi.org/10.20944/preprints202303.0350.v1 Topaloglu, R.O. Quantum Machine Learning for Ocular Disease Recognition. Preprints 2023, 2023030350. https://doi.org/10.20944/preprints202303.0350.v1
Abstract
In this paper we use quantum machine learning to detect and classify ocular diseases across age related macular degradation, cataract, diabetic, glaucoma, hypertension, and patological myopia categories versus a control group. We analyze fundus imagery from 1000 patients. Early findings indicate there may be benefit in terms of accuracy and loss function minimization of 2.07% and 1.979x respectively compared to a similar method implemented using traditional computers.
Keywords
ocular; disease; quantum; machine learning; artificial intelligence; recognition; detection; classification
Subject
Medicine and Pharmacology, Ophthalmology
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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