This paper is published in Volume-6, Issue-1, 2020
Area
Intelligent System
Author
Muhammad Asif, Abeer Fatima, Asma Baloch, Shahzada Atif Naveed, Areej Fatima
Org/Univ
National College of Business Administration and Economics, Lahore, Pakistan, Pakistan
Keywords
MFIS, Creatinine, AKI, Albumin creatinine ratio, BUN, Sodium, Potassium, Chloride, Calcium, Phosphorus, Albumin, DAKI-HL-MFIS, ES
Citations
IEEE
Muhammad Asif, Abeer Fatima, Asma Baloch, Shahzada Atif Naveed, Areej Fatima. Intelligent identification of Acute kidney injury empowered with Heterogeneous Mamdani Fuzzy Inference System, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Muhammad Asif, Abeer Fatima, Asma Baloch, Shahzada Atif Naveed, Areej Fatima (2020). Intelligent identification of Acute kidney injury empowered with Heterogeneous Mamdani Fuzzy Inference System. International Journal of Advance Research, Ideas and Innovations in Technology, 6(1) www.IJARIIT.com.
MLA
Muhammad Asif, Abeer Fatima, Asma Baloch, Shahzada Atif Naveed, Areej Fatima. "Intelligent identification of Acute kidney injury empowered with Heterogeneous Mamdani Fuzzy Inference System." International Journal of Advance Research, Ideas and Innovations in Technology 6.1 (2020). www.IJARIIT.com.
Muhammad Asif, Abeer Fatima, Asma Baloch, Shahzada Atif Naveed, Areej Fatima. Intelligent identification of Acute kidney injury empowered with Heterogeneous Mamdani Fuzzy Inference System, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Muhammad Asif, Abeer Fatima, Asma Baloch, Shahzada Atif Naveed, Areej Fatima (2020). Intelligent identification of Acute kidney injury empowered with Heterogeneous Mamdani Fuzzy Inference System. International Journal of Advance Research, Ideas and Innovations in Technology, 6(1) www.IJARIIT.com.
MLA
Muhammad Asif, Abeer Fatima, Asma Baloch, Shahzada Atif Naveed, Areej Fatima. "Intelligent identification of Acute kidney injury empowered with Heterogeneous Mamdani Fuzzy Inference System." International Journal of Advance Research, Ideas and Innovations in Technology 6.1 (2020). www.IJARIIT.com.
Abstract
In this article, a new Heterogeneous-Layered Mamdani Fuzzy Inference System (HL-MFIS) is proposed to detect the Acute Kidney Injury. The proposed computerized system Detect of AKI Using Heterogeneous Mamdani Fuzzy Inference System (DAKI-HL-MFIS) Expert System, can detect the Acute Kidney Injury or No-AKI. The Expert System has two input variables at layer-I and seven input variables at layers-II. At layer-I input, variables are Creatinine and BUN that detects the output condition of a Kidney to be Normal, or Acute Kidney Injury. The further input variables at layer-II are Glomerular filtration rate, urine Albumin, sodium, potassium, chloride, calcium, and phosphorus that determine the output condition of Kidneys like Acute kidney Injury and other reasons that arise due to enzyme vaccination or due to past Kidney Injury. The overall accuracy of the DAKI-HL-MFIS Expert system is 90.5%.
