design the new system using artificial neural networks in detection of fatty liver disease

The aim of this study is to design the new system using artificial neural networks in detection of fatty liver disease. Nowadays, the most application of neural networks in medicine is in clinical and diagnostic systems. The techniques are different from the analysis of medical data and have different statistical methods such as linear and logistic regression in the field of medical data analysis. In this study, we used medical data including parameters: Age, Gender, Phosphatase, Albumin, Globumin, and Albumin to Glomobin ratio and… Two patient and healthy samples were used to determine the predictive power of characteristics, the correlation and distribution of categorical variables used in two groups of patients were first analyzed by a multidimensional test (p <0.05). According to available information from patients with fatty liver and that these patients are divided into two general categories, we compared the input and output relationships of this information using the neural network, and So, according to the model obtained in this project, it is possible to predict the newly arrived situation with a very high accuracy. Artificial Neural Networks are one of the computational methods in artificial intelligence of new computing systems and methods. The results show that the neural network model has a low error and high explanatory power and therefore has good predictive power. Now you can check the status of your liver fat by taking information in 3 questions from each person you visit.

کلیدواژه ها:

Artificial neural network ، fatty liver ، medical technology