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A project focused on exploratory data analysis (EDA) for predicting survival in cirrhosis patients. This analysis utilizes various statistical methods and visualizations to identify key factors affecting survival rates, providing insights to improve predictive modeling in healthcare.

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garimaarora15/cirrhosis-survival-prediction

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cirrhosis-survival-prediction

Objective
To conduct an Exploratory Data Analysis (EDA) aimed at investigating the distribution of clinical characteristics among patients with cirrhosis and to identify possible correlations between these characteristics and survival outcomes. The goal of this analysis is to reveal patterns and relationships within the data that may enhance predictive modeling and offer insights into the factors influencing patient survival.

Dataset Description
The dataset used in this project comes from a Mayo Clinic study on primary biliary cirrhosis (PBC) conducted from 1974 to 1984. It contains information on 424 patients with 17 clinical features, including demographics, medical history, and liver function tests.

  • Source: Mayo Clinic
  • Features: 17 clinical variables, including age, gender, lab results, symptoms, and treatment type
  • Target Variable: Survival status with values:
    • 0 = Death
    • 1 = Censored (still living without liver transplant)
    • 2 = Censored due to liver transplant

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A project focused on exploratory data analysis (EDA) for predicting survival in cirrhosis patients. This analysis utilizes various statistical methods and visualizations to identify key factors affecting survival rates, providing insights to improve predictive modeling in healthcare.

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