Call for Papers:Vol.11 Issue.4

Submission
Last date		 28-Aug-2025
Acceptance Status In One Day
Paper Publish In Two Days
Submit ManuScript

News & Updates

Submit Article

Dear Authors, Article publish in our journal for Volume-11,Issue-4. For article submission on below link: Submit Manuscript


Join As Board

Dear Reviewer, You can join our Reviewer team without given any charges in our journal. Submit Details on below link: Join As Board


Paper Publication Charges

IJARIIE APP
Download Android App

For Authors

Archives

IJARIIE Board

Downloads

Android App

Download IJARIIE APP

Authors

Title: :  Enhancing Liver Disease Diagnosis: Ensemble Techniques for Predictive Modeling and Diagnostic Strategies
PaperId: :  22083
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 9 Issue 4 2023
DUI:    16.0415/IJARIIE-22083
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Dr. Bhavesh M. PatelDepartment of Computer Science, H.N.G.University
Sirajbhai Abbasbhai NagalparaDepartment of Computer Science, H.N.G.University

Abstract

Computer Science
liver disease, Ensemble model, Data Mining, Classification Techniques
Hepatitis C is a liver illness caused by a virus that is transferred by contact with contaminated blood, most commonly through drug use and needle sharing. It can result in chronic infection, leading to serious health issues like cirrhosis and liver cancer. Symptoms may not be apparent until the disease has progressed. Prevention involves avoiding behaviors that can spread the virus, and testing is essential as treatments can cure most cases within a few months. The objective is to leverage this data to predict liver disease in patients, providing significant benefits to both medical practitioners and individuals affected by the disease. Machine learning methods are employed due to the extensive amount of data available, enabling the utilization of past data to forecast future cases. To address this, the study proposes a performance optimization strategy that considers the training data and the variables that have a significant impact on the predictive model. Logistic Regression, SVM, KNN, Random Forest, Nave Bayes, and Stacking ensemble techniques are used to train the upgraded preprocessed data. Comparative analysis is conducted on the six models and against other research models. The novel model employing stacking classifier and surpasses others, achieving remarkable testing accuracy of 96%. This showcases our approach as a practical solution for real-world liver disease detection.

Citations

Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.

IJARIIE Dr. Bhavesh M. Patel, and Sirajbhai Abbasbhai Nagalpara. "Enhancing Liver Disease Diagnosis: Ensemble Techniques for Predictive Modeling and Diagnostic Strategies" International Journal Of Advance Research And Innovative Ideas In Education Volume 9 Issue 4 2023 Page 3507-3515
MLA Dr. Bhavesh M. Patel, and Sirajbhai Abbasbhai Nagalpara. "Enhancing Liver Disease Diagnosis: Ensemble Techniques for Predictive Modeling and Diagnostic Strategies." International Journal Of Advance Research And Innovative Ideas In Education 9.4(2023) : 3507-3515.
APA Dr. Bhavesh M. Patel, & Sirajbhai Abbasbhai Nagalpara. (2023). Enhancing Liver Disease Diagnosis: Ensemble Techniques for Predictive Modeling and Diagnostic Strategies. International Journal Of Advance Research And Innovative Ideas In Education, 9(4), 3507-3515.
Chicago Dr. Bhavesh M. Patel, and Sirajbhai Abbasbhai Nagalpara. "Enhancing Liver Disease Diagnosis: Ensemble Techniques for Predictive Modeling and Diagnostic Strategies." International Journal Of Advance Research And Innovative Ideas In Education 9, no. 4 (2023) : 3507-3515.
Oxford Dr. Bhavesh M. Patel, and Sirajbhai Abbasbhai Nagalpara. 'Enhancing Liver Disease Diagnosis: Ensemble Techniques for Predictive Modeling and Diagnostic Strategies', International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 4, 2023, p. 3507-3515. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Enhancing_Liver_Disease_Diagnosis__Ensemble_Techniques_for_Predictive_Modeling_and_Diagnostic_Strategies_ijariie22083.pdf (Accessed : ).
Harvard Dr. Bhavesh M. Patel, and Sirajbhai Abbasbhai Nagalpara. (2023) 'Enhancing Liver Disease Diagnosis: Ensemble Techniques for Predictive Modeling and Diagnostic Strategies', International Journal Of Advance Research And Innovative Ideas In Education, 9(4), pp. 3507-3515IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Enhancing_Liver_Disease_Diagnosis__Ensemble_Techniques_for_Predictive_Modeling_and_Diagnostic_Strategies_ijariie22083.pdf (Accessed : )
IEEE Dr. Bhavesh M. Patel, and Sirajbhai Abbasbhai Nagalpara, "Enhancing Liver Disease Diagnosis: Ensemble Techniques for Predictive Modeling and Diagnostic Strategies," International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 4, pp. 3507-3515, Jul-Aug 2023. [Online]. Available: https://ijariie.com/AdminUploadPdf/Enhancing_Liver_Disease_Diagnosis__Ensemble_Techniques_for_Predictive_Modeling_and_Diagnostic_Strategies_ijariie22083.pdf [Accessed : ].
Turabian Dr. Bhavesh M. Patel, and Sirajbhai Abbasbhai Nagalpara. "Enhancing Liver Disease Diagnosis: Ensemble Techniques for Predictive Modeling and Diagnostic Strategies." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 9 number 4 ().
Vancouver Dr. Bhavesh M. Patel, and Sirajbhai Abbasbhai Nagalpara. Enhancing Liver Disease Diagnosis: Ensemble Techniques for Predictive Modeling and Diagnostic Strategies. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2023 [Cited : ]; 9(4) : 3507-3515. Available from: https://ijariie.com/AdminUploadPdf/Enhancing_Liver_Disease_Diagnosis__Ensemble_Techniques_for_Predictive_Modeling_and_Diagnostic_Strategies_ijariie22083.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads



Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
Real-Time Hand Gesture Recognition with Finger Counting (Using OpenCV and Mediapipe)Computer scienceBhumika Sahu Download
Diffie Hellman Key Exchange Algorithm with Man in the middle attack (MITM)Computer Science EngineeringMahesh Purushottam Gajbhiye Download
AN IMPROVED ATTRIBUTE BASED ACCESS CONTROL IN PERSONAL HEALTH RECORDS USING CLOUD WITH CONSTANT CIPHERTEXT LENGTHScience and TechBitrus Isahaka Dzarma Download
Driver Drowsiness Detection System By Measuring EAR and MARComputer Engineering Zoya Fatema Khan Download
Cloud-Based File Storage and Sharing Web ApplicationComputer Science & EngineeringMohammed Aadil Download
STUDYNEST: ONLINE LEARNING PLATFORM WITH AI RECOMMENDATION SYSTEMComputer Science and Engineering Urvashi Suresh Waghmare Download
Leveraging AWS for Developing and Hosting a Dynamic Food Ordering Web ApplicationComputer EngineeringAfshin Khanam Download
Edge-to-Cloud Synergy: An Autoencoder-GAN Framework for Anomaly Detection in Healthcare Records, Financial Statements, and Secure Cloud StorageInformation TechnologyKarthik Kushala Download
E-Commerce Fraud Detection Based on Machine Learning TechniquesComputer Science EngneeringVikram Ankush Ade Download
Detection of Phishing Website Using Gradient Boosting AlgorithmComputer Science and EngineeringYAWALKAR PRASAD PRAMOD Download
Property Dealing WebComputer Science EngineeringYash Chaudhari Download
Reinforcement Learning for the Evolution of Antimicrobial Nano formulationsmachine learningMadhusudan Download
SecuraVault: A secured blockchain based cloud storage systemComputer Engineering Anshika Jaiswal Download
Autoimmune Disease Detection in women Using Machine Learning Approachcomputer science EngineeringJ. L. V. S. Download
Medicine Overdose Detection System Using Machine LearningComputer Science EngineeringDr.Somashekhar B M Download
12