Machine Learning Based Clinical Diagnosis of Liver Patients with Instance Replacement

Authors

  • J. V. D. Prasad Department of Computer Science and Engineering, V.R. Siddhartha Engineering College, Andhra Pradesh, Vijayawada, India
  • A. Raghuvira Pratap Department of Computer Science and Engineering, V.R. Siddhartha Engineering College, Andhra Pradesh, Vijayawada, India https://orcid.org/0000-0002-1146-9387
  • Babu Sallagundla Department of Computer Science and Engineering, V.R. Siddhartha Engineering College, Andhra Pradesh, Vijayawada, India

DOI:

https://doi.org/10.13052/jmm1550-4646.1827

Keywords:

Feature Selection, Instance Replacement, Clustering

Abstract

With the rapid increase in number of clinical data and hence the prediction and analysing data becomes very difficult. With the help of various machine learning models, it becomes easy to work on these huge data. A machine learning model faces lots of challenges; one among the challenge is feature selection. In this research work, we propose a novel feature selection method based on statistical procedures to increase the performance of the machine learning model. Furthermore, we have tested the feature selection algorithm in liver disease classification dataset and the results obtained shows the efficiency of the proposed method.

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Author Biographies

J. V. D. Prasad, Department of Computer Science and Engineering, V.R. Siddhartha Engineering College, Andhra Pradesh, Vijayawada, India

J. V. D. Prasad has received the M. Tech degree in Computer Science and Engineering from V.R. Siddhartha Engineering College, Vijayawada, India. Currently pursuing Ph.D. from Department of Computer Science and Engineering from Acharya Nagarjuna University, Andhra Pradesh. His research interests include Data Mining and Parallel Computing. He has over more than 14 years of teaching experience. Currently he is working as Assistant Professor in Computer Science and Engineering at V.R. Siddhartha Engineering College, Vijayawada, India.

A. Raghuvira Pratap, Department of Computer Science and Engineering, V.R. Siddhartha Engineering College, Andhra Pradesh, Vijayawada, India

A. Raghuvira Pratap has received the B.Tech degree in Computer Science and Engineering from V.R. Siddhartha Engineering College, Vijayawada, India. He has received the M.Tech degree in Computer Science and Engineering from P V P Siddhartha Institute of Technology, Vijayawada, India and Currently pursuing Ph.D. from Department of Computer Science and Engineering from SRM Institute of Science and Technology, Tamil Nadu. His research interests include Machine Learning and Data analytics. He has over more than 12 years of teaching experience. Currently he is working as Assistant Professor in Computer Science and Engineering at V.R. Siddhartha Engineering College, Vijayawada, India.

Babu Sallagundla, Department of Computer Science and Engineering, V.R. Siddhartha Engineering College, Andhra Pradesh, Vijayawada, India

Babu Sallagundla has received the B.Tech degree in Computer Science and Engineering from Priyadarsini College of Engineering, Sulurupet, India. He has received the M. Tech degree in Computer Science and Engineering from V.R. Siddhartha Engineering College, Vijayawada, India. Currently Ph.D. from Department of Computer Science and Engineering from Sarvepalli Radhakrishnan University, Bhopal, Madhya Pradesh, India. His research interests include Machine Learning and Data Analytics. He has over more than 11 years of teaching experience. Currently he is working as Assistant Professor in Computer Science and Engineering at V.R. Siddhartha Engineering College, Vijayawada, India.

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Published

2021-11-16

Issue

Section

Enabling AI Technologies Towards Multimedia Data Analytics for Smart Healthcare