ARTIFICIAL INTELLIGENCE PREDICTION OF CHRONIC KIDNEY FAILURE

Authors

  • Ngozi Ernest-Okoye Anambra State Polytechnic, Mgbakwu. Nigeria Author
  • Ugochukwu Chinedu Odogwu Anambra State Polytechnic, Mgbakwu. Nigeria Author

Keywords:

Artificial Intelligence, Kidney failure, Chronic, Threshold, Human body.

Abstract

Adaptability and survival of the human body is dependent on the ability of separate body organs to work together as a system. The kidney as one of the important organs of the body deserves proper care to avoid failure. This research sort to simulate and postulate the threshold points of kidney failure using SEUCR test results obtained from indigenous hospitals in the Eastern part of Nigeria and synchronized in TensorFlow; an open source library for numerical computation. The result outcome is presented in realtime large-scale and verified with machine learning. A Virtual kidney diagnostic platform at 97% accuracy depicted threshold points of kidney failures.

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Published

2026-01-31

How to Cite

ARTIFICIAL INTELLIGENCE PREDICTION OF CHRONIC KIDNEY FAILURE. (2026). International Journal of Functional Research in Science and Engineering (IJFRSE) , 3(4), 89-103. https://www.journalfrse.org/journal/article/view/106

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