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Unit of study_

BMET5934: Biomedical Machine Learning

Designing artificial intelligence (AI) based systems for solving real world problems is about finding an appropriate AI tool for the task at hand. This unit aims to provide students with the opportunity to work in small groups (3-5 students per group) and design and implement an AI system that solves a real-world biomedical problem. Students will work with large database of multi-sensor biological signals from a public data source such as M.I.T Physionet or National Sleep Research Resource and design AI systems predicting desired biomedical outcomes. For example, the groups may design a system for automatic sleep staging of human sleep using electroencephalogram signals. The unit will emphasise using signal processing/machine learning tools to find practical and effective solutions to the posed biomedical problem.

Code BMET5934
Academic unit Biomedical Engineering
Credit points 6
Prerequisites:
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None
Corequisites:
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None
Prohibitions:
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None
Assumed knowledge:
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BMET2901/9901 or equivalent, and (BMET2925 or BMET9925), and (BMET3997 or BMET9997 or ELEC3305 or ELEC9305)

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

  • LO1. Communication and Inquiry/ Research: Capacity to write reports and make presentations to communicate technical and often complex material in clear and concise terms for a specific target audience.
  • LO2. Project and Team Skills: Ability to work in an interdisciplinary team effectively and efficiently by assuming clearly defined roles and responsibilities and then interacting in a constructive manner with the group by both contributing and evaluating others' viewpoints in a project where devices and software tools are deployed in a health environment.
  • LO3. Design: Be able to Conceive and Design an innovative health software application
  • LO4. Problem Solving and Inventiveness: Be able to combine signal processing methods on biological signals with appropriate machine learning algorithms to achieve required outcomes.
  • LO5. Engineering/ IT Specialisation: Be able to explain what physiological signals are and how they are measured. Show proficiency in using state of the art tools and methods to analyse sensing data.
  • LO6. Maths/ Science Methods and Tools: Be able to select and apply appropriate signal processing and machine learning methods to achieve a practical solution to a realworld biomedical problem

Unit outlines

Unit outlines will be available 1 week before the first day of teaching for the relevant session.