Liver Disease Prognosis Based on Clinical Parameters Using Machine Learning Approach
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 6
Abstract
We are living in the era of Machine Learning. The use of Machine Learning in medical diagnosis of various diseases increases many fold in recent years. In this Paper we had made an attempt to demonstrate an analytical approach for prediction of liver diseases in patients using probabilistic models of machine learning based on KSVM, SVM and KKNN. The technique used for classification and prediction are based on recognizing typical and diagnostically most important clinical features considered responsible for liver diseases. The main contributions of the research involve predicting the probability of each case against Class ‘A’ belonging to Non Diseased group and Class ‘B’ belonging to group of diseased patients. The analysis confirmed high risk and low risk patients as predicted by the probabilistic model.
Authors and Affiliations
Ayushi . , Amit Sharma, Vinod Sharma, Dr. Rajeev Gupta
Keywords
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