University develops AI solution to detect common infection in dementia patients
The University of Surrey has developed new artificial intelligence (AI) which aims to improve the identification of urinary tract infections (UTI) amongst dementia patients.
UTI is an infection of the urinary system, with symptoms including pain in the lower part of stomach, blood in urine, needing to urinate suddenly and more often than normal, and changes in mood and behaviour. It is one of the most common causes for hospitalisation for people living with dementia.
Scientists from the University of Surrey’s Centre for Vision, Speech and Signal Processing (CVSSP) used a technique called Non-negative Matrix Factorisation to find hidden clues of possible UTI cases. The team then used machine learning algorithms to identify early UTI symptoms.
The experiment was part of the TIHM (Technology Integrated Health Management) for dementia project, led by Surrey and Borders Partnership NHS Foundation Trust and in collaboration with the University of Surrey and industry partners.
Part of the NHS Test Beds Programme and funded by NHS England the Office for Life Sciences, the project saw clinicians remotely monitor the health of dementia patients living at home. This was enabled by a network of devices, such as environmental and activity monitoring sensors.
Data streamed from these devices was then analysed using machine learning solutions and the identified health problems were flagged on a digital dashboard and followed up by a clinical monitoring team.
Payam Barnaghi, Professor of Machine Intelligence at CVSSP, said: “Urinary tract infections are one of the most common reasons why people living with dementia go into hospital. We have developed a tool that is able to identify the risk of UTIs so it is then possible to treat them early.
“We are confident our algorithm will be a valuable tool for healthcare professionals, allowing them to produce more effective and personalised plans for patients.”