Title: "Optimizing Cancer Treatment with Multi$-$Armed Bandits

Problem Statement:

You are a data scientist working in cancer research, collaborating with a medical

institution that conducts clinical trials for different treatment protocols. The objective is

to optimize the allocation of resources $($Research time, and funding$)$ across diverse

treatment arms within breast cancer clinical trials. The primary goal is to identify the

most efficacious and personalized treatment strategies while minimizing resource

expenditure and expediting the development of effective treatments for cancer patients.

Consider the following aspects:

Treatment Arms and Patient Response: Each treatment arm represents a different

treatment technique $($Harmone Therapy, Radiation Therapy, Chemotherapy and Surgery$).$

Different arms might have varying efficacies $($Treatment status $$ Either success $($Value $1)$

or Failure $($Value $0)),$ cancer characteristics such as radius, texture etc., budget and

treatment duration.

Requirements and Deliverables:

$1.$ Elaborate on$,$ how cancer treatment clinical trial problem is related with Multi

armed bandit problem and explain the strategy to solve the problem. Let the

detailed description be in a Word document. $(2$ Marks$)$

$2.$ Prepare a Colab sheet with outputs saved satisfying the following requirements.

Implementation should be in OpenAI gym with python.

$($a$)$ Using the given dataset $($Link given at end of the page$),$ model the effectiveness

of different treatment arms based on treatment status. $(2$ Marks$)$

$($b$)$ Implement the multi$-$armed bandit algorithm to dynamically allocate patients

to different treatment arms to maximize the discovery of effective treatments

while minimizing risks and costs. Consider constraints such as the maximum

number of patients that can be assigned to each arm, ethical considerations, and

the need for statistical significance in trial outcomes. $(3$ Marks$)$

$($c$)$ Evaluate the performance of your algorithm by measuring metrics such as the

identification of the most effective treatment arm, time$-$to$-$discovery, patient

safety, and overall cost$-$effectiveness. $(1$ Mark$)$