METHOD FOR CONSTRUCTING A DECISION TREE FOR DIAGNOSING EPILEPSY IN CHILDREN

Авторы

  • Maryam Midharara Автор
  • Nozimakhon Kuchkarova Автор

Ключевые слова:

expert system, electroencephalography, epilepsy, decision tree, method, algorithm, program.

Аннотация

A method and algorithm for constructing a decision tree for diagnosing epilepsy in children are proposed. The analysis and processing of medical data, consisting of electroencephalogram indicators, rhythms and provocative tests, which make it possible to determine the type of epilepsy in children, was carried out. The proposed algorithmic and software allows you to determine the type of epilepsy in children with a reliability and efficiency of 95%.

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Библиографические ссылки

Kononenko W, “Machine learning for medical diagnosis: history, state of the art and perspective, Artificial Intelligence in Medicine”. Ljubjana 2001. P. 89-109..

Ramesh A. N. et al. ”Artificial intelligence in medicine,” Annals of The Royal College of Surgeons of England. – 2004. – Т. 86. – №. 5. – С. 334.

Patel V. L. et al. ”The coming of age of artificial intelligence in medicine,” Artificial intelligence in medicine. – 2009. – Т. 46. – №. 1. – С. 5-17.

Furmankiewicz M., Sołtysik-Piorunkiewicz A., Ziuziański P. “Artificial intelligence systems for knowledge management in e-health: the study of intelligent software agents,” Latest Trends on Systems:The Proceedings of 18th International Conference on Systems, Santorini Island, Greece. – 2014, – С. 551-556.

Kumar S., Kaur G, “Detection of heart diseases using fuzzy logic,” International Journal of Engineering Trends and Technology. – 2013. – Т. 38. – №. 6. – С. 2694-2699.

ONUWA O. B. Fuzzy, “Expert System for Malaria Diagnosis,” ORIENTAL JOURNAL OF COMPUTER SCIENCE & TECHNOLOGY. - 2014. - №7(2). - С. 273-284.

Kaur R., Kaur A,”Hypertension diagnosis using fuzzy expert system,” International Journal of Engineering Research and Applications (IJERA) National Conference on Advances in Engineering and Technology, AET-29th March. – 2014.

Kirillov V., Gladyshev A., Demidchik E, ”Technology of Creation of an Expert System for Diagnosing Thyroid Pathology Based on a Set of Qualitative Signs of Cell Atypia,” Microscopy Research and Technique. 2010. №73. С. 1091–1100.

Bell G. S., Neligran A., Sander J. W, “An unknown quantity –the worldwide prevalence of epilepsy,” Journal of Epilepsia. 2014; 55 (7): 958-962.

GBD 2016 Epilepsy Collaborators (2019). Global, regional and national burden of epilepsy, 1990–2016: a systematic analysis for the Global Burden of Disease Study. Lancet Neurol. 18: 357–375.

WHO Epilepsy Factsheet. Updated February 2017. Accessed: 03.02.2017. 8. URL:http://www.who.int/mediacentre/factsheets/fs999/en/.

R.B. Azizova Abdullayeva N.N. Usmonalieva I.I. Neuroimmunological Characteristics of Idiopathic and Symptomatic Epilepsy in Accordance with the Clinical Course. Medico-Legal Update. An International journal Volume 20, Number 4 October-December 2020. Р 1377-1383.

Wheless, James & Clarke, Dave & Arzimanoglou, Alexis & Carpenter, Daniel. (2008). Treatment of pediatric epilepsy: European expert opinion, 2007. Epileptic disorders : international epilepsy journal with videotape. 9. 353-412.

Sanei Saeid and Chambers J.A. EEG signal processing, Centre of Digital Signal Processing Cardiff University, UK – John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ, England, 2007. – C. 289.

Adeli H., Zhou Z., Dadmehr N, ”Analysis of EEG records in an epileptic patient using wavelet transform,” J. Neurosci. Methods. 2003. Vol. 123, no. 1, P. 69- 87.

Khan Y.U., Gotman Y, “Wavelet based automatic seizure detection in intracerebral electroencephalogram,” Clin. Neurophysiol. 2003. Vol. 114, no. 4, P. 898-908.

Wavelet-crosscorrelation analysis: non-stationary analysis of neurophysiological signals, Mizuno-Matsumoto Y. [et al], Brain Topogr. 2005. Vol. 17, no. 4, P. 237-252.Chen H., Nui H, "Detection of character wave in EEG by wavelet,” J. Electronic Sci. Technol. 2004. Vol. 2, no. 2, P. 269-271.

D’Atellis C.E., Isaacson S.I., Sime R.O, “Detection of epileptic events in electroencephalograms using wavelet analysis,” Ann. Biomed. Eng. 1997. Vol. 25, P. 286-293.

Senhadji L., Wendling F. “Epileptic transient detection: wavelets and timefrequency approaches,” Neurophysiol. Clin. 2002. Vol. 32, no. 3, P. 175-192.

Fast wavelet transformation of the EEG / Schiff S.J. [et al] , ‘Electroencephalography and Clinical Neurophysiology’, 1994. Vol. 91, no. 6, P. 442- 455.

Опубликован

2024-04-10

Выпуск

Раздел

Естественные науки

Как цитировать

METHOD FOR CONSTRUCTING A DECISION TREE FOR DIAGNOSING EPILEPSY IN CHILDREN. (2024). Инновации в науке и технологиях, 1(3), 369-376. https://innoist.uz/index.php/ist/article/view/362

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