PET/MR User's Meeting: Technical challenges Feb 05, 2020 10:30 AM - 03:00 PM — Henry Wellcome Auditorium, 183 Euston Road, London
Scottish Ophthalmic Imaging Society meeting Feb 14, 2020 09:30 AM - 05:00 PM — Royal Society of Edinburgh, 22-26 George Street, Edinburgh
Scottish+ Radiotherapy Physics Meeting 2020 Feb 21, 2020 09:30 AM - 05:00 PM — Scottish Health Service Centre , Western General Hospital, Edinburgh
2nd Scottish Ultrasound Annual Scientific Meeting Feb 28, 2020 10:00 AM - 05:00 PM — Collins Building, University of Strathclyde
Technology Innovations for Healthcare Mar 12, 2020 09:00 AM - 05:00 PM — Royal College of Physicians, Edinburgh

eLearning

SINAPSE experts from around Scotland have developed ten online modules designed to explain medical imaging. They are freely available and are intended for non-specialists.


Edinburgh Imaging Academy at the University of Edinburgh offers the following online programmes through a virtual learning environment:

Neuroimaging for Research MSc/Dip/Cert

Imaging MSc/Dip/Cert

PET-MR Principles & Applications Cert

Applied Medical Image Analysis Cert

Online Short Courses

PhD studentship at Aberdeen: Trust in artificial intelligence for health care diagnostics

Accountability and transparency in AI: Application to Health Care Diagnostics

Artificial Intelligence (AI) is set to transform health care. Innovation projects are underway in Scotland as part of iCAIRD - Industrial Centre for Artificial Intelligence Research in Digital Diagnostics - including an exemplar project in Aberdeen to develop computer assisted technology to detect abnormalities in X-ray or CT scan radiology images assisting in the early diagnosis of breast cancer.

However, there is increasing recognition that AI systems should not be dealt with as a “black box”. For successful translation into clinical practice, trust, transparency and accountability of AI systems are emerging as key components. Clear definition of AI system strengths and weaknesses, accuracy, bias and reliability are important. The optimal methods to explain AI systems for health care remain uncertain but there is growing evidence from other domains.

This PhD offers a mixed methods approach, bringing together a multidisciplinary supervisory team with expertise in computing science, qualitative methodology and health informatics within the Centre for Health Data Science. The PhD also offers the opportunity for an industrial placement with Canon Medical to understand how the methodology being developed in the PhD could be introduced into state of the art AI assisted health digital technologies.

For details of this project with Prof C Black, Dr N Oren, and Prof L Locock at the University of Aberdeen, go to https://www.findaphd.com/phds/project/accountability-and-transparency-in-ai-application-to-health-care-diagnostics/?p106836

The deadline for application is 22 March 2019