Our researchers in The London Medical Imaging and AI Centre for Value-Based Healthcare have been working on many uses for artificial intelligence (AI) in health and are pushing boundaries of technological advancement in imaging equipment and the capabilities of modern software, resulting in both improvements in care and the wealth of data.
Making earlier and more accurate diagnoses
Medical imaging has been an integral part of healthcare for decades due to its ability to offer non-invasive ways of diagnosing and monitoring patients for signs of disease.
Each hospital Trust hold millions of these images – Guy’s and St Thomas’ NHS Foundation Trust holds 5.5 million – but AI can be used as a decision support tool for the radiology teams, who currently have to analyse each record manually.
Through the use of neural networks, algorithms can be trained to process thousands of imaging files to a strict classification system. In addition, as the algorithms process the visual information at pixel scale, they can flag very incremental differences to volume and structure which are not necessarily visible to the naked eye.
Indeed, in work published earlier this year, teams from King’s & Guy’s and St Thomas’ NHS Foundation Trust cut the reporting time for X-rays to receive expert radiologist opinion, from 11 to less than 3 days.
The same concept is also being applied to antenatal ultrasound scans, where AI can be used to identify abnormalities in the fetal heart and lungs.
Improving surgical outcomes
Machine learning, another subset of AI, has been shown to be highly effective in the operating room through the creation of 3D computer models of patients’ own organs, which mean surgeons can plan more effectively for complex surgery. When combined with advances in image and sensor guidance technologies these same models can be used in real-time during the procedure itself.