Decision support systems
  • 2019 № 1 Prediction of development of inflammatory complications in patients with an urolithiasis in the postoperative period

    It is developed diagnostically – the prognostic way of assessment of risk of development of inflammatory complications
    of the postoperative period in patients with an urolithiasis based on results of prospektivny inspection of 1240 patients. When carrying out the multiple-factor analysis the following markers influencing development of complications in the postoperative period were revealed: SOE, LII level, index of an albumin, expressiveness of a proteinuria and leukocyturia, existence of signs of system inflammatory reaction, violation of an urodinamika and hydronephrosis. Points which during conducting diagnostic testings summarized were appropriated to these signs. On the basis of an original way the computer program having high diagnostic value is created.

    Authors: Berezhnoi A. G. [1] Yu. S. Vinnik [1]

    Tags: inflammatory complications1 prediction2 urolithiasis2

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  • Artificial intelligence in health care
  • 2019 № 4 Prediction of recurrence in patients with Cushing’s disease after successful endoscopic transnasal adenomectomy: neural network model and its software implementation

    Introduction. Due to the high frequency of recurrences in patients with Cushing’s disease after endoscopic transnasal adenomectomy (up to 55% in the 5 year period), it is important to develop a method for predicting recurrence of the disease based on a combination of factors. Мaterials and methods. The study included 219 patients who underwent endoscopic transnasal adenomectomy in 2007–2014.Over 3 years, remission persisted in 172 patients; relapse developed in 47 patients. The construction of artificial neural networks of various topologies was performed in the Statistica v. 13, and then software was developed for the best network.
    Results. A highly efficient neural network (3-layer perceptron) was constructed, which allows predicting recurrence within 3 years or remission for at least 3 years. The sensitivity of the model is 74%, the specificity 97%, the positive predictive value 85%, the negative predictive value 93%. The predictors of the model are sex, age, duration of the disease, MRI type of adenoma, levels of adrenocorticotropic hormone and cortisol in blood in early postoperative period. Web-calculator was developed and is available to doctors for free practical use on http://medcalc.appspot.com/.
    Сonclusion. The software implementing neural network is a quite effective tool for predicting recurrence and it will allow to perform personalized approach to management of patients who underwent neurosurgical treatment for the Cushing’s disease.

    Authors: Nadezhdina E. Y. [1] O. Yu. Rebrova [2] Antyukh M. S. [1] Grigoriev A. Y. [1]

    Tags: artificial neural network2 prediction2 recurrence1 software calculator1 web-based application1 сushing disease1

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