DTS306TC Security, Privacy and Ethics Coursework 2| Solved
Overview
Artificial intelligence has great effect on modern lives. In this coursework, the theme on framework design
of new medical image-based bias-mitigated and fair computer-aided diagnosis system will be investigated
and explored. The coursework consists of two parts. In Part 1, you need to complete a report based given
theme. In Part 2, you need to explain your design via video presentation.
Part 1 (Individual Report: 70 marks)
Healthcare industry is rich of electronic (digital) medical data from different modalities. Deep learning has
revolutionized the use of machine learning in healthcare industry by leveraging on the model’s automatic
feature extraction and learning. To date, deep models have been applied for numerous computer-aided
diagnosis tasks such as prediction, detection and classification. Despite its promising outlook, deep learningbased computer-aided diagnosis models still fail to earn the trust of medical doctors. In fact, there are
reports of inaccurate missed diagnoses due to bias error, lack of understanding about the underlying
mechanism of deep learning, and miscalibration in real practice. Therefore, there is an open call for fair
and transparent computer-aided diagnosis model for trustworthy smart healthcare.
The aim of this task is to empirically assess the current status of computer-aided diagnosis, technologies,
challenges and solutions in smart healthcare, and research questions in AI fairness to design a towards
innovative bias-mitigated and fair deep learning medical image-based computer-aided
diagnosis model framework design with predefined traits. Hence, you are required to equip yourselves
with the understanding about the specific domain of medical imaging. Besides, you need to apply the knowledge acquired from the lectures and tutorials to complete this coursework. You also need to do
literature review to identify further relevant information that is helpful to develop your report content.
Task Instructions:
(1) You are required to study the medical image-based artificial intelligence computer-aided diagnosis
by using deep learning in smart healthcare domain. Therefore, literature review is needed. For
beginner, you can refer to the suggested review paper to understand the domain of smart
healthcare using AI:
Most Nilufa Yeasmin, Md Al Amin, Tasmim Jamal Jati, Zeyar Aung & Mohammad Abdul Azim. 2024.
Advanced of AI in Image-Based Computer-Aided Diagnosis: A Review. Array. 23(2024) 100357.
Available Online: https://doi.org/10.1016/j.array.2024.10035
Moreover, you are required to study extra learning materials to familiarize yourselves with imagebased computer-aided diagnosis by using deep learning. Please note that no mark will be given to
the literature review nor content extract from the given review paper. However, this effort shall
serve as your first steep for your proposed towards innovative bias-mitigated and fair deep
learning medical image-based computer-aided diagnosis model framework design.
(2) Write a report on your proposed towards innovative bias-mitigated and fair deep learning
medical image-based computer-aided diagnosis model framework design. The report
should be written in a clear and concise manner with no more than 1,500 words+/-5%. in total
length. Your final report should be detailed, relevant and rationale in addressing the following
sections:
Part 2 (Individual Presentation: 30 marks)
Task Instructions:
(1) Prepare and record a short individual presentation video of 5 minutes+/-5%. Your presentation
should be clear, should be in no more than 10 Powerpoint slides and should not take beyond
5 minutes+/-5%. The presentation should address the followings:
i. To introduce and explain the significance of your proposed towards innovative biasmitigated and fair deep learning medical image-based computer-aided
diagnosis model framework design.
ii. To explain how your proposed model design can effectively become General Data
Protection Regulation (GDPR) and IEEE “Human Standards” with Implications
for AI compliance in order to promote your design to overseas healthcare market
successfully.
Report Format:
Cover Page: This should include the Assessment Number, Assessment Title, Student Name, Student ID
and Student Email
Body of the report: This should include all the relevant section headings to address each section as
indicated above and marking rubrics.
References: Both your in-text and the references included in the “References” section at the end of the
report should adhere strictly to the IEEE reference style.
Formatting requirement:
- Use multiple spacing: 1.08 and spacing after: 8pt;
- Use a standard 12-point font, font type: Tahoma
- Use “Justify” body text
- Put your page numbers at the top right (except the cover page)
- Most importantly, always run a spelling and grammar check; however, remember, such checks
may not pick up all errors. You should still edit your work manually and carefully.