Deploying AI in the Clinic: Thinking about the box
As machine learning scientists working in healthcare, we get very excited about both the potential of AI technology and the results that can be achieved with it currently. However, good performance does not guarantee clinical use. In this talk, I will present some considerations that must be addressed in translating technical research into clinical products. While many of the challenges remain the same regardless of the technology used, I will focus specifically on the impact that AI has on reaching the clinic, giving examples from our experience at Mirada in commercialising deep learning-based autocontouring.
Dr Mark Gooding, Chief Scientist at Mirada Medical, obtained his DPhil in Medical Imaging from University of Oxford in 2004. He was employed as a postdoctoral researcher both in university and NHS settings, where his focus was largely around women’s health. In 2009, he joined Mirada Medical, motivated by a desire to see technical innovation translated into clinical practice. While there, he has worked on a broad spectrum of clinical applications, developing algorithms and products for both diagnostic and therapeutic purposes. If given a free choice of research topic, his passion is for improving image segmentation, but in practice he is keen to address any technical challenge. Dr Gooding now leads the research team at Mirada, where in addition to the commercial work he continues to collaborate both clinically and academically.
Dr Gooding has been responsible for leading the research and the development of DLCExpert™ technology, which uses AI (Artificial Intelligence) to learn the clinician’s contouring preferences and automatically apply them to images. This technology demonstrates that AI is not just about huge technological leaps forward. It can be more rapidly applied to everyday tasks to make incremental step-change improvements to the effectiveness of radiotherapy treatment planning, saving time for oncologists and potentially improving patient care.