PL EN


2018 | 2 | 171-175
Article title

On an algorithm for decision-making for the optimization of disease prediction at the primary health care level using neural network clustering

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EN
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References
  • Mintzer OP, Woronenko YV, Babintseva LY, et al. Health informatization concept in Ukraine. Medical Informatics and Engineering 2012;3: 5–29.
  • Epstein RM, Franks P, Fiscella K, et al. Measuring patient-centered communication in patient-physician consultations: theoretical andpractical issues. Soc Sci Med 2005; 61: 1516–1528
  • Schiff GD. Minimizing diagnostic error: the importance of follow-up and feedback. Am J Med 2008; 21(5, Suppl.): S38–S42.
  • Wong D, Galleqos Y, Weinger M, at al. Changes in intensive care unit nurse task activity after installation of a third-generation intensive care unit information system. Crit Care Med 2003; 31(10): 2488–2494.
  • Perera C. The evolution of e-Health – mobile technology and mHealth. JMTM 2012; 1(1): 1–3, doi: http://dx.doi.org/10.7309/jmtm.1.
  • Vostrov GN, Mintser ОP, Pavlov ОО, et al. Information model of remote medical services. The first message. Medical Informatics and care unit information system. Crit Care Med 2003; 31(10): 2488–2494.
  • Hartzband P, Groopman J. Off the record − avoiding the pitfalls of going electronic. N Engl J Med 2008; 358: 1656–1658.
  • Martsenyuk VP, Kravets NO. On the software development environment of intelligent medical databases. Clinical Informatics and Telemedicine 2004; 1: 47–53.
  • Florczak B, Scheurich A, Croghan J, et al. An observational study to assess an electronic point-of-care wound documentation and reporting system regarding user satisfaction and potential for improved care. Ostomy Wound Manage 2012; 58(3): 46–51.
  • Kovalchuk LA. Results of the latest techniques of the educational process in the I. Horbachevsky Ternopil State Medical University and system regarding user satisfaction and potential for improved care. Ostomy Wound Manage 2012; 58(3): 46–51.future plans. Med Educ 2012; 2: 11–17
  • Martsenyuk V. On an indirect method of exponential estimation for a neural network model with discretely distributed delays. Electron J Qual Theo 2017; 23: 1–16, doi: 10.14232/ejqtde.2017.1.23.
  • Martsenyuk V. Indirect method of exponential convergence estimation for neural network with discrete and distributed delays. EJDE 2017; 246: 1–12. Available from URL: https://ejde.math.txstate.edu/Volumes/2017/246/martsenyuk.pdf
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Publication order reference
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YADDA identifier
bwmeta1.element.desklight-bea35a2f-ad87-4ac5-8dca-59cb5aa325e5
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