Abstract:

Liver is a vital function in the individual body. Artificial Intelligence widely helps to identify the complex medical imaging of the affected liver as it helps the radiologist as well the physicians to do their task with accuracy. The liver diseases are diagnosed by using the popular methods like tissue biopsy, blood test, ultrasound effects, CT scan, MRI to identify its damages and for the further treatments. In this paper consolidated the last five years’ efforts in the field of liver diagnosis using the affected liver medical imaging with the help of artificial Intelligence and neural networks algorithms. The proposed study is to diagnosis the liver whether it is normal or it gets affected by the diseases through the classification techniques to identify the normal and abnormal liver using neural network algorithms and to do the necessary feature selection by using the nature inspired algorithms. Then the result will compare with two CNN algorithms and analyze the efficiency of the accurate percentage to identify the liver diseases

Description:

Machine Learning, Support Vector Machine, K-Nearest Neighbor, Neural Network, Decision Tree, Random Forest,Literature Review, Comparison of Algorithm & Performance Proposed Methodology