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Unit of study_

HTIN4005: Applied Healthcare Data Science

2024 unit information

The current health data revolution promises transformative advancements in healthcare services and delivery. However, the data generated are vast and complex. Extracting actionable understanding requires cross-disciplinary engagement between data science with healthcare. This unit explores the computational technologies involved in integrating and making sense of the breath of health data, and their use in better understanding the patient. Students will understand the data challenges presented by the various assays in which patients are quantified, spanning genetic testing to organ imaging. Students will explore how computational and machine learning models can span health data to derive integrated understanding of the links and patterns across them. They will employ such models in performing diagnosis and forecasting disease progression and intervention outcomes, thus enabling personalised medicine and supporting clinical decision making. This unit will develop students' understanding of current healthcare challenges, how these can be framed as data science questions, and how they can engage and apply their knowledge in cross-disciplinary ventures to improve healthcare.

Unit details and rules

Managing faculty or University school:

Engineering

Study level Undergraduate
Academic unit Computer Science
Credit points 6
Prerequisites:
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132 credit points
Corequisites:
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None
Prohibitions:
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HTIN5005
Assumed knowledge:
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None

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

  • LO1. Demonstrate knowledge of the broad range of computational problems in healthcare.
  • LO2. Use machine learning tools to address the needs in healthcare data science.
  • LO3. Evaluate the performance of machine learning tools in computational healthcare problems.
  • LO4. Apply and tailor known machine learning tools for solving new challenging healthcare problems.
  • LO5. Present the design and evaluation of a machine learning prototype for healthcare data science problems, defining the requirements and describing the design processes and evaluation.
  • LO6. Communicate and collaborate effectively across technological and healthcare/medicine disciplinary boundaries.

Unit availability

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Session MoA ?  Location Outline ? 
Semester 2 2024
Normal evening Camperdown/Darlington, Sydney
Outline unavailable
Session MoA ?  Location Outline ? 
Semester 2 2023
Normal evening Camperdown/Darlington, Sydney

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Modes of attendance (MoA)

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