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Liver Disease Prediction

Liver Disease Prediction

Price : 10000

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Course Duration
Approx 10

Course Price
₹ 10000

Course Level

Course Content

Abstract:

Chronic Liver Disease is the leading cause of global death that impacts the massive quantity of humans around the world. This disease is caused by an assortment of elements that harms the liver. For example, obesity, an undiagnosed hepatitis infection, alcohol misuse. Which is responsible for abnormal nerve function, coughing up or vomiting blood, kidney failure, liver failure, jaundice, liver encephalopathy and there are many more. Liver Diseases account for over 2.4% of Indian deaths per annum.This disease diagnosis is very costly and complicated. Therefore, the goal of this work is to evaluate the performance of different Machine Learning algorithms in order to reduce the high cost of chronic liver disease diagnosis by prediction.

 

So we proposed a system with the help of machine learning techniques and algorithms like Logistic Regression, KNN, Random Forest, Decision Tree , XGB Classifier and  Naïve Bayes to predict Liver Disease based on different parameters entered by the user in the front end.

Introduction:

The largest organ in an abdomen is the liver in the shape of triangular. The two parts of the liver is left and right hemi liver. It is a single organ. Liver used to essential for function our body. This is the primary organ for maintaining the chemicals like glucose, balancing the so many nutrients, fat, vitamins, cholesterol and hormones. In an early stage of the liver problem diagnostician will increase the survival rate of the patient. Suffering from liver disease has been rapidly increasing due to excessive drink of alcohol, inhale polluted gas, drugs, contamination food and packing food pickle, so the medical expert system will help a doctor to automatic prediction. With the repeated development in machine learning technology, early prediction of liver disease is possible so that people can easily diagnosis the deadly disease in the early stage. This will give more useful in the Healthcare department and also a medical expert system can be used in a remote area. The liver plays a very important role in life which supports the removal of toxins from the body. So early prediction is very important to diagnosis the disease and recovers.

It is very difficult to identify in early stages of liver disease even liver tissue has damaged moderately, in these case many medical expert system difficult to identify the disease. This leads to fail in treatment and medication. In order to avoid this early prediction is crucial to give proper treatment and save life of patient. There are different symptom of chronic liver disease are digestion problem including abdominal pain, dry mouth, constipation and internal bleeding, Dermatological issues like yellowish skin color, spider like veins, redness on feet and Brain and Nervous system abnormalities like memory problem, numbness and fainting. So some of the precaution to take prevention from liver disease are get regular doctor visit, get vaccinated, less soda and alcohol consumption, regular exercise and maintain weight. As per the existing system of medical expert system for diagnosis of liver disease has been useful to the society, moreover easy detection and prediction of the disease can be easy done with the use of the expert system. With the repeated improving in Artificial intelligence different types of machine learning algorithm has been developed this will help in improving the quality and accuracy of the detection or prediction of the liver disease. So detection of liver disease in early stages is very important and crucial because it will help in early treatment.

So we proposed a system with the help of machine learning techniques and algorithms like Logistic Regression, KNN, Random Forest, Decision Tree , XGB Classifier and  Naïve Bayes to predict Liver Disease based on different parameters entered by the user in the front end.

 

 

 

 

 

 

 

 

 

 

Objective:

The main aim of this project to predict the Liver Disease using machine learning techniques and algorithms like Logistic Regression, KNN, Random Forest, Decision Tree, XGB Classifier and Naïve Bayes based on different parameters entered by the user in the front end.


Problem Statement

Chronic Liver Disease is the leading cause of global death that impacts the massive quantity of humans around the world. This disease is caused by an assortment of elements that harms the liver. For example, obesity, an undiagnosed hepatitis infection, alcohol misuse. Which is responsible for abnormal nerve function, coughing up or vomiting blood, kidney failure, liver failure, jaundice, liver encephalopathy and there are many more. Liver Diseases account for over 2.4% of Indian deaths per annum.This disease diagnosis is very costly and complicated. Therefore, the goal of this work is to evaluate the performance of different Machine Learning algorithms in order to reduce the high cost of chronic liver disease diagnosis by prediction.


 

Proposed System:

 

We proposed a system with the help of machine learning techniques and algorithms like Logistic Regression, KNN, Random Forest, Decision Tree , XGB Classifier and  Naïve Bayes to predict Liver Disease based on different parameters entered by the user in the front end.

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