Author Login IJIRT Partner Network (IPN) Login

Liver Cirrhosis Detection System

  • Unique Paper ID: 167514
  • Volume: 11
  • Issue: 3
  • PageNo: 1444-1448
  • Abstract:
  • Liver cirrhosis is a highly infectious blood-borne illness that is often asymptomatic in its early stages. As a result, diagnosing and treating patients during the early stages of illness is challenging. As the illness progresses to its latter stages, diagnosis and therapy become increasingly challenging. The purpose of this work is to offer an artificial intelligence system based on machine learning algorithms that may assist healthcare practitioners in making an early diagnosis of liver cirrhosis. Various machine learning algorithms are being developed with this in mind to forecast the possibility of a liver cirrhosis infection. In this research, we deploy XGboost and Logistic Regression and with the help of EDA we will be able to predict liver cirrhosis.The model includes the use of plotly express for the visualization techniques which is highly interactive and provides comprehensive insights to our model. The model makes use of Cirrhosis Detection Dataset from Kaggle. Several model comparisons have shown their robustness, and the scheme may be determined from the research analysis.
Download article email to a friend

Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 3
  • PageNo: 1444-1448

Liver Cirrhosis Detection System

Related Articles

12 Aug, 2024

AI Toolkit for Parkinson's Disease Detection using Gait Data by Deep Learning

Read More
Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

Join Our IPN

IJIRT Partner Network

Submit your research paper and those of your network (friends, colleagues, or peers) through your IPN account, and receive 800 INR for each paper that gets published.

Join Now

Latest Publication

Archive

View More

Recent Conferences

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024 Last Date: 15th March 2024

Submit inquiry