Diagnostics (Dec 2022)

Is It Possible to Analyze Kidney Functions, Electrolytes and Volemia Using Artificial Intelligence?

  • Danijela Tasić,
  • Katarina Đorđević,
  • Slobodanka Galović,
  • Draško Furundžić,
  • Zorica Dimitrijević,
  • Sonja Radenković

DOI
https://doi.org/10.3390/diagnostics12123131
Journal volume & issue
Vol. 12, no. 12
p. 3131

Abstract

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Markers used in everyday clinical practice cannot distinguish between the permanent impairment of renal function. Sodium and potassium values and their interdependence are key parameters in addition to volemia for the assessment of cardiorenal balance. The aim of this study was to investigate volemia and electrolyte status from a clinical cardiorenal viewpoint under consideration of renal function utilizing artificial intelligence. In this paper, an analysis of five variables: B-type natriuretic peptide, sodium, potassium, ejection fraction, EPI creatinine-cystatin C, was performed using an algorithm based on the adaptive neuro fuzzy inference system. B-type natriuretic peptide had the greatest influence on the ejection fraction. It has been shown that values of both Na+ and K+ lead to deterioration of the condition and vital endangerment of patients. To identify the risk of occurrence, the model identifies a prognostic biomarker by random regression from the total data set. The predictions obtained from this model can help optimize preventative strategies and intensive monitoring for patients identified as at risk for electrolyte disturbance and hypervolemia. This approach may be superior to the traditional diagnostic approach due to its contribution to more accurate and rapid diagnostic interpretation and better planning of further patient treatment

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