Developing your Advanced Pharmacy Practice &amp; Portfolio (PHAY0049)

The aim of this module is to equip pharmacists with key skills to develop and demonstrate advanced pharmacy practice. Pharmacists completing this module will develop a critical understanding of the use of professional development frameworks as a tool for continuing professional development, and how to advance knowledge, understanding and professional development through critical reflective practice. Through development of a portfolio, pharmacists completing this module gain insight into the practical application of professional development theories and policy. Pharmacists are encouraged to identify areas for development in consultation with their peers.

This module is completed by pharmacists on the advanced professional practice route of the MSc in Advanced Pharmacy Practice (MScAPP) and is usually completed over one to two years. It can also be studied as a stand-alone short course over one year.

Artificial intelligence can assist surgeons and other healthcare professionals when performing modern computer-assisted medical procedures.

This module will...

Artificial Intelligence for Surgery and Intervention (MPHY0043)

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.