A Survey on Classification Techniques in Data Mining for Analyzing Liver Disease Disorder

Data mining is the process of extracting meaningful information from large database. In Medical field the problem may arise in the era data mining has vital role to predict and diagnosis the disease in early stage with the use of machine learning tool. Liver is the largest internal organ in the human metabolism plays an important role in human body and doing several vital functions. Liver disease may cause symptoms like Jaundice, Tendency to bruise, Bleed easily, Ascites, Impaired brain function, General failing health. The Liver disease is caused by the person who takes more alcohol in short time. Types of liver disease are Acute liver failure, Hepatitis, Liver Cancer, and Cirrhosis. In India many men’s were affected by liver disease disorder. This paper describes survey on classification techniques in data mining for analyzing liver disease disorder. Keywords— Data Mining, Liver Disease Disorder Data Set, Data Mining in Medical, Classification Techniques.

[1]  N. B. Venkateswarlu,et al.  A Critical Study of Selected Classification Algorithms for Liver Disease Diagnosis , 2011 .

[2]  Bendi Venkata Ramana,et al.  Liver Classification Using Modified Rotation Forest , 2012 .

[3]  Q. T. Islam,et al.  Etiological and Clinical Patterns of Isolated Hepatomegaly at Rajshahi, Bangladesh , 2012 .

[4]  G.Sophia Reena,et al.  Analysis of Liver Disorder Using Data mining Algorithm , 2010 .

[5]  J. Colombel,et al.  Hepatic steatosis revealing celiac disease: a case complicated by transitory liver failure. , 1996, The American journal of gastroenterology.

[6]  C. Jothi Venkateswaran,et al.  Estimating the Surveillance of Liver Disorder using Classification Algorithms , 2012 .

[7]  Shapla Rani Ghosh,et al.  A Critical Study of Selected Classification Algorithms for Liver Disease Diagnosis , 2016 .

[8]  Hoon Jin,et al.  Decision Factors on Effective Liver Patient Data Prediction , 2014, BSBT 2014.

[9]  S. Janakiraman,et al.  A Study of Textural Analysis Methods for the Diagnosis of Liver Diseases from Abdominal Computed Tomography , 2013 .

[10]  Hyontai Sug,et al.  Improving the prediction accuracy of liver disorder disease with oversampling , 2012 .

[11]  Cory J. Butz,et al.  A Foundational Approach to Mining Itemset Utilities from Databases , 2004, SDM.

[12]  Rong-Ho Lin,et al.  An intelligent model for liver disease diagnosis , 2009, Artif. Intell. Medicine.

[13]  A. Noraziah,et al.  Prediction of hepatitis prognosis using Support Vector Machines and Wrapper Method , 2010, 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery.

[14]  S. Dhamodharan.  Liver Disease Prediction Using Bayesian Classification , 2014 .

[15]  Johannes Fürnkranz,et al.  Decision Tree , 2010, Encyclopedia of Machine Learning and Data Mining.