ORIGINAL RESEARCH

Developing an artificial intelligence-based system for medical prediction

Sakhibgareeva MV, Zaozersky AYu
About authors

COMTEK LLC, Ufa, Russia

Correspondence should be addressed: Margarita Sakhibgareeva
ul. Bekhtereva 16, kv. 48, Ufa, Russia, 450047; moc.liamg@1102lv.atiragram

About paper

Contribution of the authors to this work: Sakhibgareeva MV — data processing and analysis, analysis of literature, research, drafting of a manuscript; Zaozersky AYu — research planning, data interpretation, drafting of a manuscript.

Received: 2017-11-23 Accepted: 2017-12-13 Published online: 2018-01-23
|
  1. Gusev AV. [Рerspectives of neural networks, and deep machine learning to create solutions for healthcare]. Doctor and information technologies. 2017; (3): 92–105. Russian.
  2. Kononenko I. Machine learning for medical diagnosis: history, state of the art and perspective. Artificial Intelligence in Medicine. 2001; 23(1): 89–109.
  3. Bledzhiants GA, Sarkisian MA, Isakova IA, Tumanov NF, Popov AN, Begmurodova NS. [The key technologies of artificial intelligence in medicine]. Remedium. Magazine about the Russian market of medicines and medical equipment. 2015; (12): 10–5. Russian.
  4. [Machine learning helps physicians to make more informed decisions]. Telemedicina.ru [Internet]. 2017 Sep. [cited 2017 Sep 4]. Available from: https://telemedicina.ru/news/equip/mashinnoe-obuchenie-pomojet-vracham-prinimat-bolee-informirovannyie-resheniya. Russian.
  5. Zharikov OG, Meshcherikov IV, Litvin AA. [Neuronet technologies in medicine]. The issues of organization and Informatization of healthcare. 2007; 4 (53): 59–63. Russian.
  6. Golovachev V. Oshibochniy diagnoz. Trud. 2014 Oct 28. Russian.
  7. Korotaev IG, Chernukhin GA, the authors; COMTEK Ltd., assignee. Software complex «Healthcare». The certificate of official registration program for computer 2007613347. 2007 Aug 9.
  8. Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O et al. Scikit-learn: Machine Learning in Python. Journal of Machine Learning Research. 2011; 12: 2825–30.
  9. Shalev-Shwartz S, Ben-David S. Understanding Machine Learning: From Theory to Algorithms. New York: Cambridge University Press; 2014. 410 p.
  10. Müller AC, ‎Guido S. Introduction to Machine Learning with Python: A Guide for Data Scientists. 1st ed. O'Reilly Media; 2016. 285 p.
  11. Luo Y, Szolovits P, Dighe AS, Baron JM. Using Machine Learning to Predict Laboratory Test Results. Am J Clin Pathol. 2016 Jun; 145 (6): 778–88. DOI: 10.1093/ajcp/aqw064.
  12. Khlivnenko LV, Piatakovich FA. [The option of constructing the system of collective human-machine intelligence for big data processing in medicine]. Health and Education Millenium. 2016; 18 (12): 141–4. Russian.
  13. Bilenko AA, Rybkin SV. [The application of machine learning algorithms to identify high risk diabetes type 1 diabetes]. E-magazine: science, technology and education. 2017; 1 (10): 44–9. Russian.
  14. Tseng CJ, Lu CJ, Chang CC, Chen GD, Cheewakriangkrai C. Integration of data mining classification techniques and ensemble learning to identify risk factors and diagnose ovarian cancer recurrence. Artif Intell Med. 2017; (78): 47–54.
  15. Oniśko A, Druzdzel MJ. Impact of precision of Bayesian network parameters on accuracy of medical diagnostic systems. Artif Intell Med. 2013 Mar; 57 (3): 197–206. DOI: 10.1016/j.artmed.2013.01.004.
  16. Khajehali N, Alizadeh S. Extract critical factors affecting the length of hospital stay of pneumonia patient by data mining (case study: an Iranian hospital). Artif Intell Med. 2017 Nov; 83: 2–13. DOI: 10.1016/j.artmed.2017.06.010.
  17. Weiss JC, Natarajan S, Peissig PL, McCarty CA, Page D. Machine Learning for Personalized Medicine: Predicting Primary Myocardial Infarction from Electronic Health Records. AI Magazine. 2012; 33 (4): 33–45.
  18. Futoma J, Sendak M, Cameron B, Heller K. Predicting Disease Progression with a Model for Multivariate Longitudinal Clinical Data. In: Proceedings of the 1st Machine Learning for Healthcare Conference; 2016 Aug 19-20; Children's Hospital LA, USA; 2016; (56): 42–54.