YURAK-QON TOMIR KASALLIKLARINI BASHORAT QILISH VA TASHXIS QO‘YISH INTELLEKTUAL TIZIMI

Authors

  • Xidirova Charos Murodilloyevna Muhammad al-Xorazmiy nomidagi Toshkent Axborot Texnologiyalari Universiteti
  • Jabborova Nozima Sattor qizi Muhammad al-Xorazmiy nomidagi Toshkent Axborot Texnologiyalari Universiteti

Keywords:

Bashorat qilish, ma’lumotlarni intellektual tahlil qilish, neyron tarmoq, optimallashtirish, sun’iy intellekt, tashxis qo‘yish, yurak-qon tomir kasalliklari, xavf omillari

Abstract

Maqolada, yurak-qon tomir kasalliklarini bashorat qilish va tashxis qo‘yishda intelektual tizimlarni ishlab chiqish masalasi yoritilgan. Kasalliklarni bashorat qilish, tashxis qo‘yish hamda yurak-qon tomir kasallilarini paydo bo‘lishini va uni rivojlanib borishini nazorat qilishda neyro-ekspert tizimini ishlab chiqish taklif etiladi. Intelektual tizim yordamida bemor holatini bashorat qilish va bemorlarning turmush tarzini o‘zgartirish va ayrim dori-darmonlarni qabul qilish orqali bemor sog‘lig‘ini naorat qilish aniq misollarida ko‘rsatilgan. O‘tkazilgan tajriba natijalarga ko‘ra, intellektual tizim nazorat ta’sirining oqibatlari bemorlarning jinsi va yosh xususiyatlariga va ularning hozirgi sog‘lig‘iga bog‘liqligi aniqlangan.

References

Amato F., López F., Peña-Méndez E.M., Vaňhara P., Hampl A., Havel J. Artificial neural networks in medical diagnosis // Journal of applied biomedicine. No 11. pp. 47-58. 2013. DOI 10.2478/v10136-012-0031-x.

Sandhu I.K., Nair M., Shukla H., Sandhu S.S. Artificial neural network: an emerging diagnostic tool for breast cancer // International Journal of Pharmacy and Biological Sciences. 2015. Vol. 5. Issue 3. pp. 29-41.

Narang S., Verma H.K., Sachdev U. A Review of Breast Cancer Detection using ART Model of Neural Networks // International Journal of Advanced Research in Computer Science and Software Engineering. 2012. Vol. 2, Issue 10. pp. 311-319.

Awwalu J., Garba A.G, Ghazvini A., Atuah R. Artificial Intelligence in Personalized Medicine Application of AI Algorithms in Solving Personalized Medicine Problems // International Journal of Computer Theory and Engineering. 2015. Vol. 7. No. 6, December. pp. 439-443.

Мустафаев A.Г. Применение искусственних нейронних сетей для ранней диагностики заболевания сахарним диабетом // Кибернетика и программирование. 2016. № 2. пп. 1-7.

Soltani Z., Jafarian A. A New Artificial Neural Networks Approach for Diagnosing Diabetes Disease Type II // International Journal of Advanced Computer Science and Applications. 2016. Vol. 7. No 6. pp. 89-95.

Хидирова Ч.М., Жабборова Н.С., Шоимова С.Ж. Модель прогнозирования сердечных заболеваний с использованием выбора признаков и классификации. // Иқтисодиёт тармоқларининг инноватсион ривожланишида ахборот-коммуникатсия технологияларининг аҳамияти. Республика илмий-техник анжумани маърузалар тўплами. 1-қисм. Тошкент, 2022. -бб. 201-205.

Kuo R.J., Huang M.H., Cheng W.C., Lin C.C., Wu Y.H. Application of a two-stage fuzzy neural network to a prostate cancer prognosis system // Artificial Intelligence in Medicine. 2015. No 63(2). pp. 119-133.

Sanoob M.U., Madhu A., Ajesh K.R., Varghese S.M. Artificial neural network for diagnosis of pancreatic cancer // International Journal on Cybernetics & Informatics (IJCI). 2016. Vol. 5, No. 2. pp. 40-49.

Ganesan N., Venkatesh K., Rama M.A., Malathi Palani A. Application of Neural Networks in Diagnosing Cancer Disease Using Demographic Data // International Journal of Computer Applications. 2010. Vol.1. No. 26. pp. 75-85.

Afshar S., Abdolrahmani F., Tanha F.V., Seif M.Z., Taheri K. Recognition and prediction of leukemia with Artificial Neural Network // Medical Journal of Islamic Republic of Iran. 2011. Vol. 25. No. 1. May. pp. 35-39.

Mahesh C., Suresh V.G., Babu M. Diagnosing Hepatitis B Using Artificial Neural Network Based Expert System // International Journal of Engineering and Innovative Technology. 2013. Vol. 3. Issue 6. pp. 139-144.

Khidirova Ch., Ruzibaev O., Shoimova S. Intelligent System of Diagnosing and Predicting Cardiovascular Diseases. International Conference on Information Science and Communications Technologies. Tashkent, Uzbekistan, 2022. DOI:10.1109/ICISCT55600.2022.10146803

Kadhim Q. Artificial Neural Networks in Medical Diagnosis // International Journal of Computer Science. 2011. Vol. 8. Issue 2. pp. 150-155.

Kumar K., Abhishek. Artificial Neural Networks for Diagnosis of Kidney Stones Disease // International Journal of Information Technology and Computer Science. 2012. No 7. pp. 20-25.

Gil D., Johnsson M. Diagnosing Parkinson by using artificial neural networks and support vector machines. Global Journal of Computer Science and Technology, 2009. No 9 (4). pp. 63-71.

Singh M., Singh M., Singh P. Artificial Neural Network based classification of Neuro-Degenerative diseases using Gait features. International Journal of Information Technology and Knowledge Management. 2013. Vol. 7. №1. pp. 27-30.

Aравин О.И. Применение искусственних нейронних сетей для анализа патологий в кровеносних сосудах // Российский журнал биомеханики. 2011. Т. 15. № 3 (53). пп. 45–51.

Sayad A.T., Halkarnikar P.P. Diagnosis of heart disease using neural network approach // International Journal of Advances in Science Engineering and Technology. 2014. Vol. 2. Issue 3. pp. 88-92.

Ajam N. Heart Diseases Diagnoses using Artificial Neural Network//Network and Complex Systems.2015.Vol.5.No.4. pp.7-11.

Olaniyi E.O., Oyedotun O.K. Heart Diseases Diagnosis Using Neural Networks Arbitration // International Journal of Intelligent Systems and Applications. 2015. No 12. pp. 75-82.

Kojuri J., Boostani R., Dehghani P., Nowroozipour F., Saki N. Prediction of acute myocardial infarction with artificial neural networks in patients with nondiagnostic electrocardiogram // Journal of Cardiovascular Disease Research. 2015. Vol 6. Issue 2. Apr-Jun. pp. 51-60.

Хидирова Ч.М., Жабборова Н.С. Применение искусственного интеллекта в клинических исследованиях сердечно-сосудистых заболеваний. European Journal of interdisciplinary Research and Development. -Poland. Volume 17, 2023.

Basit A., Sarim M., Raffat K.,etc. Artificial Neural Network: A Tool for Diagnosing Osteoporosis. Research Journal of Recent Sciences. 2014. Vol. 3(2).pp.87-91.

Raji, C.G., Vinod Chandra, S.S. Graft survival prediction in liver transplantation using artificial neural network models // Journal of Computational Science. 2016. No 16. pp. 72-78.

Прохоренко И.О. Метод нейросетевого моделирования и его исполъзование для прогнозирования развития соматической патологии у лиc старших возрастних групп// Современние проблеми науки и образования. 2013. № 1. URL: https://www.science-education.ru/ru/article/view?id=8411

Ясниcкий Л.Н., Думлер A.A., Богданов К.В., Полешҳук A.Н., Черепанов Ф.М., Макурина Т.В., Чугайнов С.В. Диагностика и прогнозирование течения заболеваний сердечно-сосудистой системй на основе нейронних сетей // Медиcинская теҳника. 2013. № 3. пп. 42-44.

Yasnitsky L.N., Dumler A.A., Poleshchuk A.N., Bogdanov C.V., Cherepanov F.M. Artificial Neural Networks for Obtaining New Medical Knowledge: Diagnostics and Prediction Cardiovascular’s Disease Progression// Biology and Medicine.2015.7(2):BM-095-pp.15,8.

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Published

2024-02-28

How to Cite

Xidirova , C., & Jabborova, N. (2024). YURAK-QON TOMIR KASALLIKLARINI BASHORAT QILISH VA TASHXIS QO‘YISH INTELLEKTUAL TIZIMI. DIGITAL TRANSFORMATION AND ARTIFICIAL INTELLIGENCE, 2(1), 167–175. Retrieved from https://dtai.tsue.uz/index.php/dtai/article/view/v2i125