Outline

Overview

Information technology (IT) has significantly contributed to the research and practice of medicine, biology and health care. The IT field is growing enormously in scope with biomedicine taking a lead role in utilising the evolving applications to its best advantage. The goal of this unit of study is to provide students with the necessary knowledge to understand the information technology in biomedicine. The major emphasis will be on the principles associated with biomedical digital imaging systems and related biomedicine data processing, analysis, visualisation, registration, modelling, retrieval and management. A broad range of practical integrated clinical applications will be also elaborated.

Unit details and rules

Academic unit	Computer Science
Credit points	6
Prerequisites ?	DATA3888 or COMP3888 or COMP3988 or CSEC3888 or ISYS3888 or SOFT3888 or ENGG3112 or SCPU3001
Corequisites ?	None
Prohibitions ?	COMP5424
Assumed knowledge ?	A major in a computer science area
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Weidong Cai, tom.cai@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2026

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Written exam	Final exam Supervised final exam	55%	Formal exam period	2 hours	AI prohibited
Outcomes assessed:
Creative work	Assignment-2 MIC module development	20%	Week 13 Due date: 25 May 2026 at 23:59	n/a	AI allowed
Outcomes assessed:
Creative work	Assignment-1 ITB technical report	13%	Week 13 Due date: 25 May 2026 at 23:59	n/a	AI allowed
Outcomes assessed:
Practical skill	Lab activities lab check point (via Canvas submission)	12%	Weekly	n/a	AI allowed
Outcomes assessed:
= hurdle task ?

Assessment summary

It is a requirement of the School of Computer Science that in order to pass this unit, a student must achieve at least 40% in the written examination. For subjects without a final exam, the 40% minimum requirement applies to the corresponding major assessment component specified by the lecturer. A student must also achieve an overall final mark of 50 or more. Any student not meeting these requirements may be given a maximum final mark of no more than 45 regardless of their average.

The assessment consists of (1) weekly ITB computing lab activities with lab check point (LCP) submission; (2) ITB technical report writing; (3) medical image computing (MIC) module development based on lab practice; and (4) supervised final exam.听Detailed information for each assessment can be found on the Canvas site.

Assessment criteria

The University awards common result grades, set out in the听听(Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100	听
Distinction	75 - 84	听
Credit	65 - 74	听
Pass	50 - 64	听
Fail	0 - 49	When you don鈥檛 meet the learning outcomes of the unit to a satisfactory standard.

听

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the听Academic Integrity Policy.

Visit the听Current Students website听for more information on AI in assessments, including听details on how to acknowledge its use.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

No late submission is accepted for lab check point (LCP) submission.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website听provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the听Academic Honesty Education Module (AHEM)听which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the听Current Students website听for more information on AI in assessments, including听details on how to acknowledge its use.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a听simple extension.鈥� The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can鈥檛 complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for听special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students,听听includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy听reflects the University鈥檚 commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Week 01	Introduction to ITB	Lecture (2 hr)
Week 02	ITB computing lab with LCP	Tutorial (1 hr)
Week 02	Medical data sampling and acquisition	Lecture (2 hr)
Week 03	Introductory programming for medical data processing and analysis; ITB computing lab with LCP	Tutorial (2 hr)
Week 04	ITB computing lab with LCP	Tutorial (1 hr)
Week 04	Medical data processing and analysis (I)	Lecture (2 hr)
Week 05	ITB computing lab with LCP	Tutorial (1 hr)
Week 05	Medical data processing and analysis (II)	Lecture (2 hr)
Week 06	ITB computing lab with LCP	Tutorial (1 hr)
Week 06	Medical data registration and fusion	Lecture (2 hr)
Week 07	ITB computing lab with LCP	Tutorial (1 hr)
Week 07	Multi-modal medical image computing	Lecture (2 hr)
Week 08	ITB computing lab with LCP	Tutorial (1 hr)
Week 08	Medical data storage and retrieval	Lecture (2 hr)
Week 09	ITB computing lab with LCP	Tutorial (1 hr)
Week 09	Medical data modeling and simulation	Lecture (2 hr)
Week 10	ITB computing lab (assignment help session)	Tutorial (1 hr)
Week 10	Molecular imaging and modelling	Lecture (2 hr)
Week 11	ITB computing lab (assignment help session)	Tutorial (1 hr)
Week 11	Molecular imaging applications	Lecture (2 hr)
Week 12	ITB computing lab (assignment help session)	Tutorial (1 hr)
Week 12	Computer-aided diagnosis: from macro to micro	Lecture (2 hr)
Week 13	Advanced medical image computing	Lecture (2 hr)

Attendance and class requirements

Attendance:听Students are expected to attend all scheduled lab/tutorials.

高清福利片 commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. apply biomedical data processing and analysis techniques to ITB real cases and applications
LO2. apply learned core ITB knowledge to solve problems and provide optimal ITB solutions
LO3. understanding key sampling and acquisition techniques for biomedical data
LO4. understand various registration and fusion approaches for biomedical data
LO5. understand the-state-of-the-art of biomedical data visualization applications
LO6. have obtained research and development skills in advanced biomedical data modelling

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one鈥檚 personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

No significant change will make.

Additional information

IMPORTANT: School guidelines relating to Academic Dishonesty and Plagiarism.听

In assessing a piece of submitted work, the School of Computer Science may reproduce it entirely, may provide a copy to another member of faculty, and/or to an external plagiarism checking service or in-house computer program and may also maintain a copy of the assignment for future checking purposes and/or allow an external service to do so.

Computer programming assignments may be checked by specialist code similarity detection software. The Faculty of Engineering currently uses the MOSS similarity detection engine (see听), or the similarity report available in ED (edstem.org). These programs work in a similar way to听TurnItIn听in that they check for similarity against a database of previously submitted assignments and code available on the internet, but they have added functionality to detect cases of similarity of holistic code structure in cases such as global search and replace of variable names, reordering of lines, changing of comment lines, and the use of white space.

All written assignments submitted in this unit of study will be submitted to the similarity detecting software program known as Turnitin. Turnitin searches for matches between text in your written assessment task and text sourced from the Internet, published works and assignments that have previously been submitted to Turnitin for analysis.听

There will always be some degree of text-matching when using Turnitin. Text-matching may occur in use of direct quotations, technical terms and phrases, or the listing of bibliographic material. This does not mean you will automatically be accused of academic dishonesty or plagiarism, although Turnitin reports may be used as evidence in academic dishonesty and plagiarism decision-making processes.

Links to important information and resources听听

Academic appeals: sydney.edu.au/students/academic-appeals.html

Canvas: canvas.sydney.edu.au

Expectations of student conduct: sydney.edu.au/students/student-responsibilities.html

Financial support: sydney.edu.au/students/financial-support.html

Learning and Teaching Policy: sydney.edu.au/policies/

Libraries: sydney.edu.au/students/libraries.html

Student administration: sydney.edu.au/study/student-administration.html

高清福利片 resources: sydney.edu.au/students/learning-services.html

Wellbeing and support: sydney.edu.au/students/health-wellbeing.html

Disclaimer

Important: the University of Sydney regularly reviews units of study and reserves the right to change the units of study available annually. To stay up to date on available study options, including unit of study details and availability, refer to the relevant handbook.

To help you understand common terms that we use at the University, we offer an .

高清福利片

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

高清福利片 commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Disclaimer

On this page

Useful links

COMP4424: Information Technology in Biomedicine

Semester 1, 2026 [Normal evening] - Camperdown/Darlington, Sydney

Overview

Unit details and rules

Teaching staff

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Attendance and class requirements

高清福利片 commitment

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Additional information

Disclaimer

On this page

Useful links