| Alison O'Neil, EngD |
| Fri 11 May 2018, 13:00 - 14:00 |
| AGB Seminar Room AGB Building, King’s Buildings, EH9 3JL |
If you have a question about this talk, please contact: Ardimas Purwita (s1600157)
Abstract:
Healthcare is a domain in which resources are low and demand is high. There is great potential for machine learning algorithms to aid clinicians in many aspects of the workflow, from acquiring better data more quickly, to detecting and quantifying disease, to deciding and planning therapies. This requires training algorithms which can match or surpass the level of expert humans. This talk will discuss the challenges in emulating the expert and how to take a disciplined scientific approach to machine learning so that theoretical concepts translate into robust real world results.
Biography:
Alison O'Neil is a scientist in the AI research team at Canon Medical Research Europe. After four years of a Medical degree at the University of Edinburgh, she finally decided that this was not her raison d’être and transferred to undertake an MEng in Electrical Engineering and Electronics. A stimulating industrial Masters placement sponsored by Canon led seamlessly to her pursuit of an Engineering Doctorate focusing on machine learning in medical imaging at Heriot-Watt University, also sponsored by Canon. As a scientist at Canon for the last 3 years, she now combines her enthusiasm for working in the healthcare domain with her natural bent for mathematics and design, and is excited to be part of the AI Research team which started in January 2018 and which has a remit to move beyond imaging data to work with all types of healthcare data.