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Description
Artificial intelligence can assist surgeons and other healthcare professionals when performing modern computer-assisted medical procedures.
This module will first provide an introduction to artificial intelligence (AI) and highly transferable skills for biomedical engineering problems, including:
- basic concepts and methodologies in contemporary machine learning (ML) and other AI applications, with a current focus on deep neural networks; and
- practical engineering aspects, from Machine Learning model selection, implementation, training, validation to deployment.
The second part of the module will introduce applied Machine Learning methods in surgery and intervention, including:
- a systematic overview of common tasks carried out during surgical procedures, examples including surgical workflow recognition, instrument localisation and intraoperative data fusion;
- hands-on experience in applying ML for these complex tasks; and
- an understanding of their challenges and limitations.
This module is designed to be highly hands-on with real-world application tutorials using modern deep learning frameworks such as TensorFlow with Keras.
Module deliveries for 2024/25 academic year
Last updated
This module description was last updated on 8th April 2024.
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