Reference no: EM133559557 , Length: 1200 Words

Data science application project

In this unit, you will complete two consecutive assignments with a focus on a specified real-world data science application.

Aim
These assignments are designed to help you develop a good understanding of the latest data-driven modeling techniques used in real-world applications, and to guide you to master the implementation of the entire data science pipeline on a given dataset using R programming language. By completing these assignments, you will gain hands-on experience and knowledge that will prepare you for future real-world data science projects.

Topic background
Dementia is a debilitating disease that affects millions of people worldwide. Early detection and risk prediction are crucial for effective treatment and care. Data-driven models are increasingly important in the field of dementia research, as they can identify patterns and relationships in complex datasets and use them to predict an individual's risk of developing the disease in an effective and efficient manner.

Mid-term assignment (individual assignment)
Who writes the review?
• Students will work independently to conduct a concise literature review on the latest data-driven models for dementia risk analysis and prediction.
What is the aim?
• The purpose of this review is to help you gain knowledge and insight into the most current data-driven approaches used in the field of dementia risk analysis and prediction, including their application and potential outcomes. This will also prepare you for data modeling to analyze the provided dementia data in Assignment 2.
What articles to review?
• You are required to review at least fivecomputing/health informatics/ehealthJOURNAL articles published date after 2020 that focus on dementia risk analysis and prediction modeling using data-driven models and analytics tools, such as statistical, machine learning and other data mining techniques.
What is the word count?
• Word limit: 1,200 words (can be within a +/- 10% range of this word limit), excluding references.
What is the structure?
• Your review should be well-structured, clearly written, and appropriately referenced. The following outline should be followed:
• Introduction:
? The introduction is used to set the context of your review. In this opening paragraph, you need to:
o Define the topic of your study and provide any relevant background information that helps your reader to understand the topic i.e., dementia.
o Explain your reason or perspective for reviewing the literature on this topic.
o By doing so, you will give your readers an idea of what to expect in your review and what and why data-driven models for dementia risk analysis and prediction are significant.
• Body:
- (Read first):
o be sure that you have sorted your reviewed articles into different themes which can be based on different analyzed data types, data-driven techniques, or the purposes of data modeling.
o Then give your sorted groups a descriptive name. The names of the sorted articles will become your headings for each of the paragraphs that you write in the body of your review.
- (Then write):
o Write an introduction paragraph for the body of your review. This paragraph tells the reader specific information on how many articles you reviewed and how you sorted the articles into common themes. This section begins with an explanation of how you have organized your small-scale literature review.
o Then, there will be separate paragraphs that describe each theme and a summary of each article including the data resources used, adopted data-driven models, findings, advantages, and weaknesses, etc. you can also compare, contrast and/or connect the articles you've selected under each theme.
• Summary:
- This is the last paragraph of your small-scale literature review. In this paragraph, it is important to summarize the main findings and insights from the review.
- You should also identify any gaps or limitations in the studies reviewed, as well as any opportunities for further research and development in this field.
• References
- This is the last page of your review. It serves as a listing of all references that you mentioned in your paper. Please use IEEE reference style when completing this list.

Attachment:- Data science application project.rar