AI-based Diagnostic Tool for Liver Disease using Machine Learning Algorithms
2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)
(2022), pp. 1-6
Rex Paolo C. Gamara
a
,
Antipas T. Teologo, Jr.
a
,
Romano Q. Neyra
b
,
Argel A. Bandala
c
a Electrical and Electronics Engineering Department, FEU Institute of Technology, Manila, Philippines
b Senior Director for Engineering Office, FEU Institute of Technology, Manila, Philippines
c Department of Electronics and Computer Engineering, De La Salle University – Manila, Manila, Philippines
Abstract: The liver is the human body's largest internal organ. Globally, liver disease is considered the cause of approximately 2 million yearly death – whereas the 11th and 16th worldwide leading causes of death are cirrhosis and liver cancer. In the Philippines, according to the Department of Health (DOH), liver cancer is ranked as the 3rd leading cause of death. In most cases, surgery may be considered a possible cure if detected at an early stage. However, there is no efficient early detection method for liver cancer. In this paper, multiple machine learning methodologies are modeled to provide diagnosis classification of liver disease based on the laboratory parameter readings. Based on the results for all models, the most accurate prediction is made by ANN at 89%, followed by SVM at 79.5%. The results establish that AI-based machine learning approaches may be utilized for assisting medical-related diagnosis.