A Review of Machine Learning Techniques for Applied Eye Fundus and Tongue Digital Image Processing with Diabetes Management System

• URL: http://arxiv.org/abs/2012.15025v1
• Date: Wed, 30 Dec 2020 03:49:37 GMT
• Title: A Review of Machine Learning Techniques for Applied Eye Fundus and Tongue Digital Image Processing with Diabetes Management System
• Authors: Wei Xiang Lim, Zhiyuan Chen, Amr Ahmed, Tissa Chandesa and Iman Liao
• Abstract summary: Diabetes is a global epidemic and it is increasing at an alarming rate. The International Diabetes Federation projected that the total number of people with diabetes globally may increase by 48%. This paper addresses the background of diabetes and its complications.
• Score: 7.209705108900718
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Diabetes is a global epidemic and it is increasing at an alarming rate. The International Diabetes Federation (IDF) projected that the total number of people with diabetes globally may increase by 48%, from 425 million (year 2017) to 629 million (year 2045). Moreover, diabetes had caused millions of deaths and the number is increasing drastically. Therefore, this paper addresses the background of diabetes and its complications. In addition, this paper investigates innovative applications and past researches in the areas of diabetes management system with applied eye fundus and tongue digital images. Different types of existing applied eye fundus and tongue digital image processing with diabetes management systems in the market and state-of-the-art machine learning techniques from previous literature have been reviewed. The implication of this paper is to have an overview in diabetic research and what new machine learning techniques can be proposed in solving this global epidemic.

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