https://github.com/sayamalt/liver-cirrhosis-stage-prediction

Successfully established a machine learning model which can determine whether an individual is vulnerable to the Cirrhosis disease or not by predicting its corresponding stage based on a unique set of medical features such as Cholesterol, Prothrombin, etc. pertaining to that person.
https://github.com/sayamalt/liver-cirrhosis-stage-prediction

exploratory-data-analysis feature-engineering hyperparameter-tuning model-deployment model-evaluation-metrics model-training multiclass-classification supervised-machine-learning

Last synced: 8 months ago
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Successfully established a machine learning model which can determine whether an individual is vulnerable to the Cirrhosis disease or not by predicting its corresponding stage based on a unique set of medical features such as Cholesterol, Prothrombin, etc. pertaining to that person.

• Host: GitHub
• URL: https://github.com/sayamalt/liver-cirrhosis-stage-prediction
• Owner: SayamAlt
• Created: 2022-06-07T21:13:29.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2022-06-08T11:11:52.000Z (over 3 years ago)
• Last Synced: 2024-12-28T08:09:54.340Z (10 months ago)
• Topics: exploratory-data-analysis, feature-engineering, hyperparameter-tuning, model-deployment, model-evaluation-metrics, model-training, multiclass-classification, supervised-machine-learning
• Language: Jupyter Notebook
• Homepage:
• Size: 5.48 MB
• Stars: 3
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Liver-Cirrhosis-Stage-Prediction

Liver cirrhosis is a widespread problem especially in North America due to high intake of alcohol. In this project, we will predict liver cirrhosis in a patient based on certain lifestyle and health conditions of a patient.


![Liver Cirrhosis Prediction](https://guires.uk/newsroom/wp-content/uploads/2019/11/Predicting-Liver-Disease.jpg)

![Liver Cirrhosis Stages](https://img.freepik.com/free-vector/informative-illustration-stages-liver-disease-leading-cirrhosis_1308-50030.jpg?w=2000)

![Liver Cirrhosis](https://image.cnbcfm.com/api/v1/image/105649172-1545937328446gettyimages-911340738.jpeg?v=1545937849&w=1600&h=900)

## Objective

In liver cirrhosis, there are mainly 4 stages which are as follows:




  
Stage 1 : Normal

  
Stage 2 : Fatty Liver

  
Stage 3 : Liver Fibrosis

  
Stage 4 : Liver Cirrhosis



The primary target is to predict the stage of the liver cirrhosis disease. The dataset consists of both numerical as well as categorical features.


## Deployed Web Application

Link: https://cirrhosis-stage-prediction.herokuapp.com/

## Context

Cirrhosis is a late stage of scarring (fibrosis) of the liver caused by many forms of liver diseases and conditions, such as hepatitis and chronic alcoholism. The following data contains the information collected from the Mayo Clinic trial in primary biliary cirrhosis (PBC) of the liver conducted between 1974 and 1984. A description of the clinical background for the trial and the covariates recorded here is in Chapter 0, especially Section 0.2 of Fleming and Harrington, Counting

Processes and Survival Analysis, Wiley, 1991. A more extended discussion can be found in Dickson, et al., Hepatology 10:1-7 (1989) and in Markus, et al., N Eng J of Med 320:1709-13 (1989).


A total of 424 PBC patients, referred to Mayo Clinic during that ten-year interval, met eligibility criteria for the randomized placebo-controlled trial of the drug D-penicillamine. The first 312 cases in the dataset participated in the randomized trial and contain largely complete data. The additional 112 cases did not participate in the clinical trial but consented to have basic measurements recorded and to be followed for survival. Six of those cases were lost to follow-up shortly after diagnosis, so the data here are on an additional 106 cases as well as the 312 randomized participants.


## Content

  

    Feature

    Description

  

  

    ID

    Unique Identifier

  

  

    N_Days

    Number of days between registration and the earlier of death, transplantation, or study analysis time in July 1986

  

  

    Status

    Status of the patient: C (censored), CL (censored due to liver tx), or D (death)

  

  

    Drug

    Type of drug: D-penicillamine or Placebo

  

  

    Age

    Age (in days)

  

  

    Sex

    M (Male) or F (Female)

  

  

    Ascites

    Presence of Ascites: N (No) or Y (Yes)

  

  

    Hepatomegaly

    Presence of Hepatomegaly: N (No) or Y (Yes)

  

  

    Spiders

    Presence of Spiders: N (No) or Y (Yes)

  

  

    Edema

    Presence of Edema: N (no edema and no diuretic therapy for edema), S (edema present without diuretics, or edema resolved by diuretics), or Y (edema despite diuretic therapy)

  

  

    Bilirubin

    Serum Bilirubin (in mg/dl)

  

  

    Cholesterol

    Serum Cholesterol (in mg/dl)

  

  

    Albumin

    Albumin (in gm/dl)

  

  

    Copper

    Urine Copper (in ug/day)

  

  

    Alk_Phos

    Alkaline Phosphatase (in U/liter)

  

  

    SGOT

    SGOT (in U/ml)

  

  

    Triglycerides

    Triglicerides (in mg/dl)

  

  

    Platelets

    Platelets per cubic (ml/1000)

  

  

    Prothrombin

    Prothrombin time in seconds (s)

  

  

    Stage

    Histologic Stage of Disease (1, 2, 3 or 4)

  

## Acknowledgements

The dataset can be found in appendix D of:


    Fleming, T.R. and Harrington, D.P. (1991) Counting Processes and Survival Analysis. Wiley Series in Probability and Mathematical Statistics: Applied Probability and Statistics, John Wiley and Sons Inc., New York.