Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Design of a Secure Blockchain Based Privacy Preserving Electronic Voting System Read chapter Read first chapter

2022 | OriginalPaper | Chapter

Prediction of Liver Patients Using Machine Learning Algorithms

Authors : Shefai Tanvir Fayaz, G. S. Tejanmayi, Yerramasetti Kanaka Ruthvi, S. Vijaya Shetty, Sharada U. Shenoy, Guruprasad Bhat

Published in: Emerging Research in Computing, Information, Communication and Applications

Publisher: Springer Singapore

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Liver diseases turn out to be lethal when detected late. This creates a dire requirement of an efficient and robust system to defy death with early detection. With machine learning setting to grow its roots in the healthcare industry, it would be a good choice to opt for it to overcome this problem. This study aims to tackle the same by applying selected machine learning algorithms on the Indian Liver Patients Dataset (ILPD), the accuracies of which are finally compared to arrive at the algorithm yielding the best results. For robust results, extensive preprocessing involving sampling, normalization, and particle swarm optimization (PSO) is performed on the data. This proceeds in J48 yielding the best result in classifying patients and non-patients of the dataset. Further, an etiological survey depicting the effect of various attributes on the dataset is presented.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter A Node Quality Based Cluster Header Selection Algorithm for Improving Security in MANET
next chapter Development of Security Performance and Comparative Analyses Process for Big Data in Cloud
Literature
1.
2.
Banu Priya M, Laura Juliet P, Tamilselvi PR (2018) Performance analysis of liver disease prediction using machine learning algorithms. Int Res J Eng Technol (IRJET) 5(1)
3.
Jacob J, Mathew JC, Mathew J, Issac E (2018). Diagnosis of liver disease using machine learning techniques. Int Res J Eng Technol (IRJET) 5(4)
4.
Sontakke S, Lohokare J, Dani R (2017). Diagnosis of liver diseases using machine learning. In: International conference on emerging trends and innovation in ICT (ICEI)
5.
Rajeswari P, Sophia Reena G (2010) Analysis of liver disorder using data mining algorithm. Glob J Comput Sci Technol 10(14) (Ver. 1.0)
6.
Baitharua TR, Panib SK (2016) Analysis of data mining techniques for healthcare decision support system using liver disorder dataset. In: International conference on computational modeling and security
7.
Aneeshkumar AS, Venkateswaran CJ (2015) A novel approach for liver disorder classification using data mining techniques. Eng Sci Int J (ESIJ) 2(1)
8.
Alfisahrin SNN, Mantoro T Data mining techniques for optimatization of liver disease classification
9.
Dash M, Liu H (1997) Feature selection for classification. Intell Data Anal
10.
Sonak A, Patankar RA (2015) A survey on methods to handle imbalance dataset. Int J Comput Sci Mob Comput 4(11)
11.
Dhamodharan S (2014) Liver disease prediction using bayesian classification. In: Special issue, 4th national conference on advanced computing, applications and technologies
12.
Budiman E, Haviluddin, Dengan N, Kridalaksana AH, Wati M, Purnawansyah Performance of decision tree C4.5 algorithmin student academic evaluation
13.
Vijayarani S, Dhayanand S (2015) Liver disease prediction using SVM and Näıve Bayes algorithms. Int J Sci Eng Technol Res (IJSETR) 4(4)
14.
Davis CP, Shiel Jr WC (2018) Liver blood tests abnormal values. MedicineNet
Metadata
Title
Prediction of Liver Patients Using Machine Learning Algorithms
Authors
Shefai Tanvir Fayaz
G. S. Tejanmayi
Yerramasetti Kanaka Ruthvi
S. Vijaya Shetty
Sharada U. Shenoy
Guruprasad Bhat
Copyright Year
2022
Publisher
Springer Singapore
Book
Emerging Research in Computing, Information, Communication and Applications

Print ISBN: 978-981-16-1337-1

Electronic ISBN: 978-981-16-1338-8

Copyright Year: 2022

DOI
https://doi.org/10.1007/978-981-16-1338-8_12