AI for Healthcare: Hero or Hindrance?
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AI for Healthcare: Hero or Hindrance?
Fri, 28/03/2025 - 13:00 to 14:00
Location:
Speaker:
Alison O'Neil
Affiliation:
Principal Scientist – Canon Medical Research Europe
Synopsis:
The recent emergence of powerful deep learning language models trained on huge real world datasets, including multimodal models combining text and image data, has opened up new possibilities for AI in healthcare. Multimodal models enable more sophisticated analysis of images of patients acquired using medical scanners such as X-Ray and Computed Tomography scanners, integrating additional text and clinical data from the patient’s record into the machine learning. However, the medical domain has stringent accuracy requirements, whilst AI models lack robustness, and errors may be difficult to spot. This talk focusses on the role of AI for radiology, and its potential to enable delivery of high quality healthcare in a society with an ageing population, rising costs, and limited resources.
Biography:
Alison O’Neil is a Principal Scientist in the AI Research Team at Canon Medical Research Europe and is an Honorary Research Fellow at the University of Edinburgh. She received her Engineering Doctorate (EngD) degree from Heriot-Watt University in 2016. Since 2015, she has worked as an industrial research scientist for Canon, in the Image Analysis and AI Research teams. Alison has 6 patents granted and has authored over 50 technical publications. She leads a team working on machine learning for medical imaging and clinical decision support, in the domains of medical image analysis, natural language processing (NLP), and multimodal AI. Her interests include robust representation learning, multimodal learning, and the integration of causal techniques and knowledge graphs with deep learning methods.