Coding Challenges

Coding Challenge: Kaplan-Meier Survival Analysis

Problem Statement:

Your task is to perform Kaplan-Meier survival analysis on a dataset containing cancer patient information. The dataset includes details such as patient demographics, dates of diagnosis, treatment received, and outcomes.

Main Challenge:

• Load the dataset from a CSV file or any suitable data format.
• Preprocess the data as necessary.
• Perform Kaplan-Meier survival analysis to estimate the survival function for the dataset.
• Calculate the survival probabilities over time using the Kaplan-Meier estimator.
• Plot the result including the censored subjects.

Bonus Task:

Conduct subgroup analyses by stratifying the data based on most relevant attributes and calculate survival probabilities for each subgroup. Justify your approach.

Coding Challenge: Reconstructing Adjacency Matrices

Problem Statement:

Your task is to reconstruct adjacency matrices from the dataset representing the upper triangles of 10x10 adjacency matrices. These entries encode the adjacency relationships between points inside cities in the given dataset. Each entry contains information about a city and the adjacency of points A-J in this city to each other in the form of binary connections.

Main Challenge:

• Read the dataset from a CSV file containing the database entries.
• Reconstruct the adjacency matrices based on the provided data.
• Add labels for the points, let them be called A-J.
• Visualize the reconstructed matrices in a command-line interface (CLI) print format.

Bonus Task:

Propose an alternative encoding of the data that might be suitable for this scenario and justify your choice. Discuss how your proposed encoding could enhance the overall solution and its implementation.