Urinary tract infections, commonly known as UTIs, usually do not pose serious health risks – when they are detected and treated early. However, when allowed to advance undetected past a certain point, a number of serious adverse outcomes can result from late or misdiagnosis of UTI.
A group of researchers from the University of Edinburgh and Heriot-Watt University are developing artificial intelligence and “socially assistive robots” to detect urinary tract UTIs earlier and ensure better patient outcomes.
UTIs affect 150 million people worldwide annually, making it one of the most common types of infection. When diagnosed early, it can be treated with antibiotics. If left untreated, UTIs can lead to sepsis, kidney damage, and even loss of life.
Diagnosis, however, can be difficult with lab analysis, a process taking up to 48 hours, providing the only definitive result. Early signs of a UTI can also be challenging to recognize because symptoms vary according to age and existing health conditions. There is no single sign of infection but a collection of symptoms which may include pain, fever, increased need to urinate, changes in sleep patterns, and tremors.
To address these concerns, the researchers are working with two industry partners from the care sector who are helping the scientists to develop machine learning methods and interactions with socially assistive robots to support earlier detection of potential infections and raise an alert for investigation by a clinician.
The project will gather continual data about the daily activities of individuals in their homes via sensors that could help spot changes in behavior or activity levels and trigger an interaction with a socially assistive robot. Known as “FEATHER,” the AI platform will combine and analyze these data points to flag potential infection signs before an individual or caretaker is even aware that there is a problem. Behavioral changes that could indicate UTI include changes in walking pace, increased frequency of urination, changes in cognitive function, or a change in sleep patterns, all of which could be noticed and documented by interaction with the assistive robot.
The AI and implementation aspects of the project will be led by Professor Kia Nazarpour, Dr. Nigel Goddard, and Dr. Lynda Webb from the University of Edinburgh. The Human-Robot Interaction aspects will be led by Professor Lynne Baillie, assisted by Dr. Mauro Dragone, from Heriot-Watt University.
Professor Kia Nazarpour, project lead and Professor of Digital Health at the School of Informatics, University of Edinburgh, said, “This unique data platform will help individuals, caretakers, and clinicians to recognize the signs of potential urinary tract infections far earlier, helping to prompt the investigations and medical tests needed. Earlier detection makes timely treatment possible, improving outcomes for patients, lowering the number of people presenting at hospital, and reducing costs to the NHS.”
How BigRio Helps Bring Advanced AI Solutions to Healthcare
Like the FEATHER project, improving disease detection, medical imaging, and diagnostics is an area where AI and machine learning are making one of the technology’s biggest impacts.
BigRio prides itself on being a facilitator and incubator for such advances in leveraging AI to improve diagnostics. In fact, it was my father’s own battle with and eventual death from lung disease that set me on my path to finding ways to use AI to provide earlier detection of serious medical conditions for improved patient outcomes.
Eventually, among our other success stories, we did collaborate with a researcher who is in the process of developing a cognitive digital twin of the human lung. Right now, that technology is being used specifically in the realm of testing inhalers for asthma patients, but like the FEATHER UTI detection tool, it has broader implications for better diagnostics and treatments for COPD and other lung diseases.
We like to think of ourselves as a “Shark Tank for AI.”
If you are familiar with the TV series, then you know that, basically, what they do is hyper-accelerate the most important part of the incubation process – visibility. You can’t get better visibility than getting in front of celebrity investors and a TV audience of millions of viewers. Many entrepreneurs who have appeared on that program – even those who did not get picked up by the sharks – succeeded because others who were interested in their concepts saw them on the show.
At BigRio, we may not have a TV audience, but we can do the same. We have the contacts and the expertise to not only weed out the companies that are not ready, as the sharks on the TV show do but also mentor and get those that we feel are readily noticed by the right people in the biomedical community.
Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.
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