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.

Cite This Article

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

Liver Cirrhosis Detection System

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