INTELLECTUAL ANALYSIS SYSTEMS OF MEDICINE INFORMATIONAS MAIN ASSISTANT OF RADIOLOGIST

Abstract

Digital analysis technologies and synthesis of data are very important in modern clinical practice. Innovative areas of medical science are also associated with an increasing flow of data and the discovery of new nosological forms. Processing information is the most important part in researching of normal and pathological structure and functions internal organs. Digital analysis technologies also apply to support a diagnosis decision, curative manipulations and warnings of potentially dangerous changes in the health status of patients. Despite the fact that neural networks were introduced into medicine in order to completely replace a specialist at the stage of diagnosis, the need for a doctor to participate in this process is undeniable. The most important option for using neural networks in medicine is the ability to create a logic circuit. The doctor receives information about the patient during a direct examination of the patient. The artificial neural network gives the result - the diagnosis, but the final decision-making right remains with the doctor. The information retrieval system in this scheme stands in order to compensate for the possible lack of knowledge of the doctor in complex and rare clinical cases and acts as a consultant. It is possible to use these algorithms in organizing medical support for the daily activities of troops (forces) with the widespread introduction of telemedicine technologies.

Keywords

neural network / sensitivity / artificial intelligence / digital technologies / analysis systems / radiology / radiation diagnostics / diagnosis

References

[1] Ежов А. И. Нейронные сети в медицине. 2003. С. 117.

[2] Владзимирский А. В. Телемедицина: Curatio Sine Tempora et Distantia. М., 2016. 663 с.

[3] Грибова В. В., Петряева М. В., Окунь Д. Б., Шалфеева Е. А. Онтология медицинской диагностики для интеллектуальных систем поддержки принятия решений. Онтология проектирования. 2018. Т. 8. № 1 (27). С. 58-73.

[4] Михеев А. Е., Фохт О. А., Хаткевич М. И. Один из подходов к формализации процесса внедрения МИС в медицинской организации. Врач и информационные технологии. 2018. № 5. С. 46-62.

[5] Стародубов В. И., Зарубина Т. В., Сидоров К. В., Алепко А. А. Формирование интегральных показателей оценки уровня информатизации медицинской организации. Врач и информационные технологии. 2018. № 1. С. 6-24.

[6] Чернов В. И., Есауленко И. Э., Родионов О. В., Семенов С. Н. Медицинская информатика. Ростов-на-Дону: Феникс, 2007. 320 с.

[7] Кульнев С. В., Солдатов Е. А., Каниболоцкий М. Н., Жуков А. А. Перспективы совершенствования медицинского обеспечения войск (сил) в современных конфликтах. Воен.-мед. журн. 2017. Т. 338. № 6. С. 4-12.

[8] STATISTICA Neural Network: Пер. с англ. Нейронные сети. М.: Горячая линия - Телеком, 2001. 182 с.

[9] Abeer Y. A., Ahmad M. A., Majid A. A. Clinical decision support system for diagnosis and management of chronic renal failure. In: Proceedings of Applied Electrical Engineering and Computing Technologies. IEEE. 2013. p. 1-6. Doi:10.1109. aeect.2013.6716440

[10] Isa Nam. Towards intelligent diagnostic system employing integration of mathematical and engineering model. In: Proceedings of International Conference on Mathematics, Engineering and Industrial Applications. AIP Publishi

[11] Musen M. A., Middleton B., Greenes R. A. Clinical decisionsupport systems. In: Biomedical informatics. Springer. 2014. p. 643-674. Doi:10.1007.978-1-4471-4474-8_22

[12] Prosperi M. C., Marinho S., Simpson A., Custovic A., Buchan I. E. Predicting phenotypes of asthma and eczema with machine learning. BMC medical genomics. 2014. 7 (1). Doi:10.1186.1755- 8794-7-s1-s7

[13] Zarandi M. H. F., Zolnoori M., Moin M., Heidarnejad H. A fuzzy rule-based expert system for diagnosing asthma. Transaction E: Industrial Engineering. 2010. 17 (2): 129-142.

[14] Абрамова И. А. и др. К вопросу о выполнении конечноэлементного анализа в CAE-системах. Наука и военная безопасность. 2016. № 3 (6). С. 59-65.

RIGHTS & PERMISSIONS

Lemeshkin R.E., Blinov V.A., Bagrova A.A., Borisov D.N., Sivashenko P.P.