Liver Disease Detection using Machine Learning
Author(s):
SOHAM KOKANE, ADITYA KADU, SAKSHI BHALERAO, ROHINI BHORDE, PROF. ANURADHA KULKARNI
Keywords:
Abstract
Liver is a very essential organ in the human body. It is essential to recognize or diagnose the disease early. This considerably aids in the early avoidance of disease with minimal medication. Conventional methods include Liver Function Tests and test results. Early detection of liver disease is very difficult. This is because symptoms of the disease become apparent only in the later stages of the disease. This system of Machine learning facilitates early disease detection, Identifying elements that lead to fatal liver impairment. Predicting the disease in its early stages is a difficult task for doctors and scientists due to the apparently sensitive signs. Effects will become apparent only when it is too late. The initiative seeks to use machine learning techniques to address this issue and improve the victims of the disease. Because there are few signs of liver disease, it is difficult to diagnose and symptoms usually do not appear until it is too late. The aim is to study and use a classification approach to distinguish between liver disease and healthy individuals, if diseased then further classified into the level of disease and its type. Also, precautions are provided for any symptoms. Consequently, ML techniques have identified liver disease in individuals.
Article Details
Unique Paper ID: 164926

Publication Volume & Issue: Volume 10, Issue 12

Page(s): 1954 - 1959
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