Estimating Risk Levels for Blood Pressure and Thyroid Hormone Using Artificial Intelligence Methods
Abstract
In this work, artificial intelligence methods aredesigned 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 NeuronFuzzy 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.
References
REFERENCES
E. Jiffri, “Relationship between lipid profile blood and thyroid
hormones in patient with type 2 diabetes mellitus,” Adv Obes Weight
Manag Control, vol. 6, no. 6, pp. 178–182, 2017. [Online]. Available:
https://doi.org/10.15406/aowmc.2017.06.00176
A. T. Azar, S. A. El-Said, and A. E. Hassanien, “Fuzzy and
hard clustering analysis for thyroid disease,” Computer methods and
programs in biomedicine, vol. 111, no. 1, pp. 1–16, 2013. [Online].
Available: https://doi.org/10.1016/j.cmpb.2013.01.002
E. Sonuc¸ et al., “Thyroid disease classification using machine
learning algorithms,” in Journal of Physics: Conference Series, vol.
, no. 1. IOP Publishing, 2021, p. 012140. [Online]. Available:
https://doi.org/10.1088/1742-6596/1963/1/012140
A. Amouzegar, M. Heidari, S. Gharibzadeh, L. Mehran, M. Tohidi,
and F. Azizi, “The association between blood pressure and normal
range thyroid function tests in a population based tehran thyroid study,”
Hormone and Metabolic Research, pp. 151–156, 2015.
H. Das, B. Naik, and H. Behera, “Medical disease analysis using neurofuzzy with feature extraction model for classification,” Informatics in
Medicine Unlocked, vol. 18, p. 100288, 2020. [Online]. Available:
https://doi.org/10.1016/j.imu.2019.100288
M. MAyilvaganan and K. Rajeswari, “Analysis study of fuzzy logic
using blood pressure readings.”
G. Arji, H. Ahmadi, M. Nilashi, T. A. Rashid, O. H. Ahmed, N. Aljojo,
and A. Zainol, “Fuzzy logic approach for infectious disease diagnosis:
A methodical evaluation, literature and classification,” Biocybernetics
and biomedical engineering, vol. 39, no. 4, pp. 937–955, 2019.
[Online]. Available: https://doi.org/10.1016/j.bbe.2019.09.004
B. S. Alyas, “Design an intelligent system for thyroid diseases
diagnosis,” International Journal of Enhanced Research in Science
Technology & Engineering, vol. 3, no. 4, pp. 217–229, 2014. [Online].
Available: https://www.researchgate.net/publication/333547166
D. Sharma, G. Singh Aujla, and R. Bajaj, “Deep neuro-fuzzy approach
for risk and severity prediction using recommendation systems in
connected health care,” Transactions on Emerging Telecommunications
Technologies, vol. 32, no. 7, p. e4159, 2021. [Online]. Available:
https://doi.org/10.1002/ett.4159
H. Abbad Ur Rehman, C.-Y. Lin, Z. Mushtaq, and S.-F. Su,
“Performance analysis of machine learning algorithms for thyroid
disease,” Arabian Journal for Science and Engineering, pp. 1–13, 2021.
[Online]. Available: https://doi.org/10.1007/s13369-020-05206-x
R. R. Yager and L. A. Zadeh, An introduction to fuzzy logic applications
in intelligent systems. Springer Science & Business Media, 2012, vol.
[Online]. Available: https://doi.org/10.1007/978-1-4615-3640-6
T. J. Ross, Fuzzy logic with engineering applications. John Wiley &
Sons, 2009. [Online]. Available: https://doi.org/10.1002/9781119994374
K. Tanaka and B. Werners, An introduction to fuzzy logic for
practical applications. Springer, 1997. [Online]. Available: https:
//doi.org/10.1002/9781119994374
N. H. Phuong and V. Kreinovich, “Fuzzy logic and its applications in
medicine,” International journal of medical informatics, vol. 62, no.
-3, pp. 165–173, 2001. [Online]. Available: https://doi.org/10.1016/
S1386-5056(01)00160-5
G. Hayward and V. Davidson, “Fuzzy logic applications,” Analyst,
vol. 128, no. 11, pp. 1304–1306, 2003. [Online]. Available:
https://doi.org/10.1039/B312701J
P. M. Larsen, “Industrial applications of fuzzy logic control,”
International Journal of Man-Machine Studies, vol. 12, no. 1, pp. 3–
, 1980. [Online]. Available: https://doi.org/10.1016/S0020-7373(80)
-2
C. Von Altrock, Fuzzy logic and neurofuzzy applications explained.
Prentice-Hall, Inc., 1995. [Online]. Available: https://dl.acm.org/doi/
abs/10.5555/201020
J. Harris, Fuzzy logic applications in engineering science. Springer
Science & Business Media, 2005, vol. 29. [Online]. Available:
https://doi.org/10.1007/1-4020-4078-4
G. Bojadziev and M. Bojadziev, Fuzzy sets, fuzzy logic, applications.
World scientific, 1995, vol. 5. [Online]. Available: https://doi.org/10.
/2867
M. Y. Al-Ridha, R. R. O. Al-Nima, and A. S. Anaz, “Adaptive
neuro-fuzzy inference system for controlling a steam valve,” in
IEEE 9th International Conference on System Engineering and
Technology (ICSET). IEEE, 2019, pp. 156–161. [Online]. Available:
https://doi.org/10.1109/ICSEngT.2019.8906307
S. Dhanasekaran, P. Mathiyalagan, and A. M. Rajeshwaran, “Automatic
segmentation of lung tumors using adaptive neuron-fuzzy inference
system,” Annals of the Romanian Society for Cell Biology, pp.
468–17 483, 2021. [Online]. Available: http://www.annalsofrscb.ro/
index.php/journal/article/view/7648
E. Ozgan, I. Korkmaz, and M. Emiro ¨ glu, “Adaptive neuro-fuzzy ˘
inference approach for prediction the stiffness modulus on asphalt
concrete,” Advances in Engineering Software, vol. 45, no. 1, pp. 100–
, 2012. [Online]. Available: https://doi.org/10.1016/j.advengsoft.
09.015
W. Liu, “Forecasting exchange rate change between usd and jpy using
dynamic adaptive neuron-fuzzy logic system,” Asia Pacific Journal of
Finance and Banking Research, vol. 2, no. 2, 2008. [Online]. Available:
https://ssrn.com/abstract=1536037
I. Crismaru, A. Pantea Stoian, O. G. Bratu, M.-A. Gaman, A. M. A.
Stanescu, N. Bacalbasa, and C. C. Diaconu, “Low-density lipoprotein
cholesterol lowering treatment: the current approach,” Lipids in
health and disease, vol. 19, pp. 1–10, 2020. [Online]. Available:
https://doi.org/10.1186/s12944-020-01275-x
B. J. Kim, S.-H. Lee, W.-S. Ryu, B. S. Kang, C. K. Kim, and
B.-W. Yoon, “Low level of low-density lipoprotein cholesterol increases
hemorrhagic transformation in large artery atherothrombosis but not in
cardioembolism,” Stroke, vol. 40, no. 5, pp. 1627–1632, 2009. [Online].
Available: https://doi.org/10.1161/STROKEAHA.108.539643
O. L. Webb, P. M. Laskarzewski, and C. J. Glueck, “Severe depression
of high-density lipoprotein cholesterol levels in weight lifters and body
builders by self-administered exogenous testosterone and anabolicandrogenic steroids,” Metabolism, vol. 33, no. 11, pp. 971–975, 1984.
[Online]. Available: https://doi.org/10.1016/0026-0495(84)90222-1
M. A. Abou-Seif and A.-A. Youssef, “Evaluation of some biochemical
changes in diabetic patients,” Clinica Chimica Acta, vol. 346, no. 2,
pp. 161–170, 2004. [Online]. Available: https://doi.org/10.1016/j.cccn.
03.030
R. R. Al-Nima, F. S. Abdullah, and A. N. Hamoodi, “Design a
technology based on the fusion of genetic algorithm, neural network
and fuzzy logic,” arXiv preprint arXiv:2102.08035, 2021. [Online].
Available: https://doi.org/10.48550/arXiv.2102.08035
J. J. Buckley, Fuzzy probabilities: new approach and applications.
Springer Science & Business Media, 2005, vol. 115. [Online].
Available: https://doi.org/10.1007/3-540-32388-0
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