EDA of Brain Glioma

Description

The proposed work was developed to analyze and understand the set of information initially. Subsequently, based on the reports, a Shiny App application was developed to analyze factors related to brain diseases and to create plots to understand the correlated attributes present in the proposed brain disease dataset and predict the life of the patient by the symptoms.

Languages and Utilities Used

• R Programming
• R-SHINY App

Output

For the EDA part, the dataset was explored using different graphical and statistical techniques such as scatterplots, bar plots, and box plots. The analysis focused on different variables, such as Age at MRI and final pathological diagnosis. It was found that most patients suffering from brain glioma were between 51 to 78 years of age, and more than 350 out of 501 patients were suffering from the deadliest type of brain glioma, Glioblastoma (wildtype).

For the prediction part, a Shiny App was created to predict the percentage of survival of the patient based on user input. It was mentioned that there can be 133,056 different predictions for patients with their conditions of disease.

Overall, the project provides a detailed analysis of brain glioma disease using a dataset and different analytical techniques in R. The Shiny App also provides a predictive model to help clinicians and patients make informed decisions.

Program walk-through:

1. EDA

Patient's age at the time of MRI

Number of patients with different types of brain glioma

2. Predition with Shiny App

Results:

Survival Prediction of patients