Heart Diagnosis

This Fuzzy Logic In this study, a fuzzy system was designed to determine the risk of heart disease. The system consists of 24 rule bases and has a MISO (Multi Input Single Output) system structure consisting of 6 inputs - single outputs. Input values of the person; age, blood pressure, cholesterol, blood sugar, LDL and HDL values. The output value consists of the “risk” Fuzzy extraction engine and the center of gravity rinser. The risk of heart disease is calculated by applying the necessary procedures to the information received from the user.

The Rules Table

Input Ranges

Input	Range	MFs
Age	0 To 100	3
Blood Pressure	0 To 220	4
Cholesterol	100 To 250	3
Blood Sugar	0 To 120	1
High Density Lipoprotein	0 To 70	3
Lowe Density Lipoprotein	0 To 190	4

Inputs

Output Range

Output	Range	MFs
Risk	0 To 45	5

Risk

Test System

I tried our model with these data 👇 and It calculated Coroner Heart Diagnosis value is 3.5 . So in this example, this people has no risk for Coroner Heart Disease.

These Defuzzification are relative to the previous inputs 👆

Represent crisp and sense something As Figure

References

• Matplotlib Python
  • https://matplotlib.org/
• Numpy Python
  • https://numpy.org/
• Skfuzzy Python
  • https://pythonhosted.org/scikit-fuzzy/
• Fuzzy inference systems
  • https://www.cs.princeton.edu/courses/archive/fall07/cos436/HIDDEN/Knapp/fuzzy004.htm

Good Videos Youtube

1. https://youtu.be/moQak7BXsI8

2. Parts

   1. https://youtu.be/MQrDmU6Sn4s (part 1)
   2. https://youtu.be/MQrDmU6Sn4s (part 2)