Treatment of Diabetes Type II Using Genetic Algorithm

Author:

Al Switi Majdoleen,Alshraideh Bahaaldeen,Alshraideh Abedalrhman,Massad Abudalla,Alshraideh MohammadORCID

Abstract

<p>Chronic diseases is an important research field because of the growth of the number of affected people around the world. When someone has diabetes, the body either does not make enough insulin or cannot use its own insulin as well as it should. This causes sugar to build up in blood leading to complications like heart disease, stroke, and neuropathy. Poor circulation leading to loss of limbs, blindness, kidney failure, nerve damage, and death. Diagnosis plays vital role in diabetes treatment otherwise it leads to long term complications in terms of costs of the treatment of the patients and leads to many risks over the patient himself as mentioned above. In this research we propose new methodology to extract the best testing sequence evaluation mechanism for helping doctors to evaluate their patient’s cases and make the best decisions about the medicine being given. We managed to create chromosomes population each of which consists of binary decision tree, as this implementation considered being the best scenario of our problem. The system proves its efficiency by applying it on 50 patients and the results shows accuracy percentage of 95.4%.</p>

Publisher

International Association of Online Engineering (IAOE)

Subject

General Engineering

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. An Efficient System for Diagnosis of Human Blindness Using Image-Processing and Machine-Learning Methods;International Journal of Online and Biomedical Engineering (iJOE);2023-08-01

2. Optimized Computational Diabetes Prediction with Feature Selection Algorithms;Proceedings of the 2023 7th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence;2023-04-23

3. Optimizing Multi-Layer Perceptron using Variable Step Size Firefly Optimization Algorithm for Diabetes Data Classification;International Journal of Online and Biomedical Engineering (iJOE);2023-04-03

4. Male and Female Hormone Reading to Predict Pregnancy Percentage Using a Deep Learning Technique: A Real Case Study;AI;2022-10-24

5. Application of Sensor Networks for Measuring Insulin Levels;International Journal of Online and Biomedical Engineering (iJOE);2020-11-30

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