Assignment Instructions

Unstructured data management.

Assessment 2 Information
Subject Code: DATA4200
Subject Name: Data Acquisition and Management
Assessment Title: Unstructured data management
Assessment Type: Report
Word Count: 1000 Words (+/-10%)
Weighting: 35 %
Total Marks: 35
Submission: via Turnitin
Due Date: Monday of Week 10, 23:55pm AEST
Your Task
This report will enable you to practice your LO1 and LO2 skills.
LO1: Evaluate ethical data acquisition and best practice with regard to project initiation
LO2: Evaluate options for storing, accessing, distributing and updating data during the life of a project
• Complete all parts below. Consider the rubric at the end of the assignment for guidance on structure and content.
• Submit the results as a Word file in Turnitin by the due date.
Assessment Description
Business Case: Artificial Intelligence (AI) in Cardiac Imaging
According to the world Health Organisation (WHO), cardiovascular disease is the leading cause of death across the globe. Cardiac image data, together with other tools, is used in the diagnosis of cardiac disease and disorders. It is now possible to apply AI algorithms to the cardiac image data in order to predict disease progression, as well as, uncovering new patterns and thus furthering clinical knowledge in this medical area.
There are now efforts to collect huge amounts of such images and share them with other medical professionals, eg. the euCanSHare project is in the process of “developing a data sharing and analytics platform to facilitate access to large-scale cardiac imaging and non-imaging data from multiple centers (www.eucanshare.eu)”.
Furthermore, experts in AI are publishing and reviewing the best AI methods for cardiac imaging. Other authors are writing on the challenges of using algorithms in this area including data protection, patient permission and AI regulation.
Source linked to title above: https://www.frontiersin.org/articles/10.3389/fcvm.2020.00137/full Frontiers in Cardiovascular Medicine have produced a special issue which discusses six applications in the area of AI in cardiac imaging. See image below.
Assessment Instructions
1. Read the editorial article at https://www.frontiersin.org/articles/10.3389/fcvm.2020.00137/full
2. Choose one of the areas of application from the image on the previous page.
3. Introduce the application area, eg. image reconstruction. (200 words, 5 marks)
4. Explain what sort of unstructured patient data could be used by an algorithm in the area you chose, eg. ultrasound images used in image reconstruction to detect anomalies. (200 words, 7 marks)
5. Discuss best practice and options for accessing, storing, sharing, documenting and maintenance of the patient data. (400 words, 15 marks)
6. Propose a question that could be asked in relation to your unstructured data and what software might help you to run AI and answer the question. (200 words, 4 marks)
REFERENCES
Make sure you have at least ten references. The KBS library is a good place to start. Use Harvard formatting. (4 marks)
Important Study Information
Academic Integrity Policy
KBS values academic integrity. All students must understand the meaning and consequences of cheating, plagiarism and other academic offences under the Academic Integrity and Conduct Policy.
What is academic integrity and misconduct?
What are the penalties for academic misconduct?
What are the late penalties?
How can I appeal my grade?
Click here for answers to these questions:
http://www.kbs.edu.au/current-students/student-policies/.
Word Limits for Written Assessments
Submissions that exceed the word limit by more than 10% will cease to be marked from the point at which that limit is exceeded.
Study Assistance
Students may seek study assistance from their local Academic Learning Advisor or refer to the resources on the MyKBS Academic Success Centre page. Click here for this information.
Assignment Submission
Students must submit their individual analysis as a Microsoft Word document via Turnitin on Monday of Week 10 at 23:55pm AEST. Students are also encouraged to submit their work well in advance of the time deadline to avoid any possible delay with Turnitin similarity report generation or any other technical difficulties.
Late assignment submission penalties
Penalties will be imposed on late assignment submissions in accordance with Kaplan Business School’s Assessment Policy.
Number of days Penalty
1* – 9 days 5% per day for each calendar day late deducted from the student’s total Marks.
10 – 14 days 50% deducted from the student’s total marks.
After 14 days Assignments that are submitted more than 14 calendar days after the due date will not be accepted and the student will receive a mark of zero for the assignment(s).
Note Notwithstanding the above penalty rules, assignments will also be given a mark of zero if they are submitted after assignments have been returned to students.
*Assignments submitted at any stage within the first 24 hours after deadline will be considered to be one day late and therefore subject to the associated penalty.
If you are unable to complete this assessment by the due date/time, please refer to the Special Consideration Application Form, which is available at the end of the KBS Assessment Policy:
https://www.kbs.edu.au/wp-content/uploads/2016/07/KBS_FORM_AssessmentPolicy_MAR2018_FA.pdf
Section Criteria NN (Fail)
0%-49% P (Pass)
50%-64% CR (Credit) 74%-65% DN (Distinction) 75%-84% HD (High
Distinction)
85%-100%
1. Introduction of
application
(5 marks) Students will introduce one of the applications of AI in cardiac imaging Not relevant
Too general Basic introduction as in paper
Very little research Solid introduction as in
paper
Evidence of adequate research Logical informative introduction which flows well
Partially integrated with the rest of the report Logical informative introduction which is well integrated with the rest of the report
Explanation about potential data (7 marks) Not relevant or not unstructured data
Too general Adequate suggestions about data but may be
vague
Good ideas about potential data Specific ideas about potential data
Well explained Specific and novel ideas about potential data
Explained in an engaging way
Best practice for access, storage, sharing, documenting and maintenance of data (15 marks) Not relevant
Too general, parts missing General ideas as in
lecture
Very little research
All parts addressed in a logical way
Reasonable research All parts addressed in a in a logical and flows
with other sections
Well researched All parts addressed in a in an integrated way and flows with other sections
Deep and novel research
Questions in relation to data
(4 marks) Question not relevant
Too general Question very general
and may not be practical
Software general Question practical, clear and relevant
Software connects better to question Question practical, clear and relevant
Software well suited to
answer the question
Some research about the need for the answer Question practical, clear, novel and relevant
Software well suited to answer the question and may have
examples on how to apply it
Good research about
the need for the answer
Page 5 Kaplan Business School Assessment Outline
Referenc structure (4 marks) es and Just enough basic searched references in correct
Well thought out structure with flair Deeply researched references in correct format.
Well thought out structure with flair and originality
At least ten references. Use Harvard formatting.
Report must be well structured Not enough or irrelevant references
Poor format
Report not well structured references
Generally correct format
Ordered structure Good references in
correct format
Good overall structure Well re
format
Comments:
Page 6 Kaplan Business School Assessment Outline
Page 7 Kaplan Business School Assessment
Outline

Unstructured data management

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