Prediction and Analysis of Liver Patient Data Using Linear Regression Technique

  • Deepankar Garg
  • Akhilesh Kumar Sharma
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 705)


In the current scenario, it is very difficult for the doctors to diagnose liver patient and there should be some kind of automated support based on machine intelligence that can help to diagnose in advance so that doctors start the treatment faster and save time. The machine intelligence is a way to predict the liver-related problems; in this study, the linear regression is used to predict the same, more accurately. The albumin levels are highly related in diagnosing these kinds of liver problems. The proposed model worked efficiently on 583 observations provided as well as on new datasets. The total average accuracy achieved in this proposed model was 89.34% which is much more than the previously identified research work of Wold et al. (SIAM J Sci Stat Comput, 5(3), 735–743, 1984, [1]) of 84.22%.


Liver patient Albumin Regression data mining model R-Miner 


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© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Computer Science & EngineeringManipal UniversityJaipurIndia
  2. 2.Department of Information TechnologyManipal UniversityJaipurIndia

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