International Journal of Advanced Science Computing and Engineering
Vol. 1 No. 1 (2019)

Online Diagnose System for Risk of Kidney Failure

Mohd Noh, Noraziah (Unknown)
Zakaria, Zalmiyah (Unknown)
Kasim, Shahreen (Unknown)



Article Info

Publish Date
30 Apr 2019

Abstract

Renal or kidney failure, only a few citizen alert in this renal failure problem. They have a lot of thing to done, and disregard on their healthy matter, especially on organ healthy that it cannot be see directly on our eyes. On that matter, online Diagnosis Renal Failure system is developed to help society to diagnose their healthy on renal failure view. System is developed online to give an advantage to society to achieve or access the system everywhere. System has two major module, diagnosis module and information module. Diagnosis module is the part where the user can make a diagnose. Information module has two sub modules, information on renal failure and information on dialysis center all around city in peninsular Malaysia. The system development is performed on expert system methodology with prototyping as the model. Production rules technique is used to represent knowledge and for searching process pattern matching technique has been use. The system expectantly can give a benefit to society and performing diagnosis in represent the knowledge of expert in medical field.

Copyrights © 2019






Journal Info

Abbrev

IJASCE

Publisher

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

Description

The journal scopes include (but not limited to) the followings: Computer Science : Artificial Intelligence, Data Mining, Database, Data Warehouse, Big Data, Machine Learning, Operating System, Algorithm Computer Engineering : Computer Architecture, Computer Network, Computer Security, Embedded ...