Musab T.S. Al-Kaltakchi is with the (e-mail: m.t.s.al kaltakchi@uomustansiriyah.edu.iq ) Raid Rafi Omar Al-Nima and Azza Alhialy are with the (e-mail: raidrafi3@ntu.edu.iq & azzakays@ntu.edu.iq).

被引：0

作者：

Al-Kaltakchi, Musab T. S. ^{[1
]}

Al-Nima, Raid Rafi Omar ^{[2
]}

Alhialy, Azza ^{[2
]}

机构：

[1] Mustansiriyah Univ, Coll Engn, Dept Elect Engn, Baghdad, Iraq

[2] Northern Tech Univ, Tech Engn Coll Mosul, Mosul, Iraq

来源：

INTERNATIONAL JOURNAL OF ELECTRONICS AND TELECOMMUNICATIONS | 2024年 / 70卷 / 03期

关键词：

blood pressure; thyroid hormone; Artificial Inteligence; Fuzzy Logic; Adaptive Neuron-Fuzzy Inference System; FUZZY-LOGIC;

D O I：

10.24425/ijet.2024.149595

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

this work, artificial intelligence methods are designed and adopted for evaluating various risk levels of thyroid hormone and blood pressure in humans. Fuzzy Logic (FL) method is firstly exploited to provide the risk levels. Additionally, a machine learning was proposed using the Adaptive Neuron- Fuzzy Inference System (ANFIS) to learn and assess the risk levels by fusing a multiple-layer Neural Network (NN) with the FL. The data are collected for standard risk levels from real medical centers. The results lead to well ANFIS design based on the FL, which can generate such interesting outcomes for predicting risk levels for thyroid hormone and blood pressure. Both proposed methods of the FL and ANFIS can be exploited for medical applications.

引用

页码：667 / 672

页数：6