Model Building and Evaluation of Asthma Data - Report Writing - IT Assignment Help

Assignment Task

Practical Task
The task is to identify a health-related problem, an appropriate dataset for generating insight into that problem, and to select and perform an appropriate novel analysis on
the dataset. Allowing you to find a dataset gives you the work on a problem that interests you personally. On Canvas, there is a page (look on “Modules”) titled “Finding datasets to work on”, which will help you. The problem you choose for this Assessment 2 can be related to that of Assessment 1 if you wish, but this is not a requirement, they can be separate problems. It is likely that some analysis has already been performed on the dataset that you choose. You will gain the most marks if you perform a novel analysis, in terms of either techniques applied or question addressed (see Rubric for details).
 
For the task,
-Describe the broad problem. What is it you are hoping to discover or achieve with your analysis?
-Describe the dataset. What does the data capture, how much of it do you have, and where did it come from?
-Perform a computational analysis. You will need to write code for this. I will be checking that it is correct, and I may even try to execute it myself. You are strongly encouraged to use comments to guide the reader through what your code does. Write the code to be read by another person.
-Report and describe the results of your analysis using an appropriate format (tables, graphs, etc).
-Interpret the results; what did you find? Use appropriate statistical methods for your problem, this may include statistical significance, effect magnitude, or machine learning metrics, or anything else that allows you to perform a robust interpretation.
-Discuss the results. What does this mean relative to the original problem? What recommendations or decisions would you provide based on your work?

 
Avoid simply copying an analysis already done on the dataset, try to find a novel approach or angle (this will be assessed).

Learning outcomes assessed
LO1. Appreciate the healthcare ecosystem as a complex multi-scale system, spanning individuals, societies, healthcare providers and industry.
LO2. Identify the prevailing challenges in medicine and the healthcare ecosystem.
LO3. Learn how data can quantify both healthcare challenges and the diverse factors from which they emerge.
LO4. Create predictive, diagnostic and prognostic systems of healthcare outcomes through machine learning.
LO5. Use computational models to explore how healthcare outcomes emerge from contributing factors, and identify interventions for how outcomes can be improved.
LO6. Communicate and collaborate effectively across technological and healthcare/medicine disciplinary boundaries.

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